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| الذكاء الاصطناعي للمبتدئين - _رسم توضيحي بواسطة [@girlie_mac](https://twitter.com/girlie_mac)_ |
استكشف عالم **الذكاء الاصطناعي** (AI) من خلال منهج دراسي يمتد لـ 12 أسبوعًا ويشمل 24 درسًا! يتضمن دروسًا عملية، اختبارات، ومختبرات. المنهج مناسب للمبتدئين ويغطي أدوات مثل TensorFlow وPyTorch، بالإضافة إلى أخلاقيات الذكاء الاصطناعي.
استكشف عالم **الذكاء الاصطناعي** (AI) من خلال منهج دراسي يمتد على مدار 12 أسبوعًا و24 درسًا! يتضمن دروسًا عملية، اختبارات، ومختبرات. المنهج مناسب للمبتدئين ويغطي أدوات مثل TensorFlow وPyTorch، بالإضافة إلى أخلاقيات الذكاء الاصطناعي.
### 🌐 دعم متعدد اللغات
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[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](./README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**إذا كنت ترغب في دعم لغات إضافية، يمكنك الاطلاع على القائمة [هنا](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
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## انضم إلى المجتمع
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -57,10 +57,10 @@ CO_OP_TRANSLATOR_METADATA:
* حالات استخدام **الذكاء الاصطناعي في الأعمال**. يمكنك أخذ [مقدمة إلى الذكاء الاصطناعي لمستخدمي الأعمال](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) على Microsoft Learn، أو [مدرسة الأعمال للذكاء الاصطناعي](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)، التي تم تطويرها بالتعاون مع [INSEAD](https://www.insead.edu/).
* **التعلم الآلي الكلاسيكي**، الذي تم وصفه بشكل جيد في [منهج التعلم الآلي للمبتدئين](http://github.com/Microsoft/ML-for-Beginners).
* تطبيقات الذكاء الاصطناعي العملية باستخدام **[الخدمات المعرفية](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. نوصي بالبدء مع وحدات Microsoft Learn لـ [الرؤية](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)، [معالجة اللغة الطبيعية](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)، **[الذكاء الاصطناعي التوليدي باستخدام خدمة Azure OpenAI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** وغيرها.
* أطر عمل **السحابة للتعلم الآلي**، مثل [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)، [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)، أو [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). يمكنك أخذ [بناء وتشغيل حلول التعلم الآلي باستخدام Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) و[بناء وتشغيل حلول التعلم الآلي باستخدام Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* تطبيقات الذكاء الاصطناعي العملية باستخدام **[الخدمات المعرفية](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. نوصي بالبدء مع وحدات Microsoft Learn لـ [الرؤية](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)، [معالجة اللغة الطبيعية](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)، **[الذكاء الاصطناعي التوليدي مع خدمة Azure OpenAI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** وغيرها.
* أطر عمل **السحابة للتعلم الآلي**، مثل [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)، [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)، أو [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). يمكنك استخدام [بناء وتشغيل حلول التعلم الآلي باستخدام Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) و[بناء وتشغيل حلول التعلم الآلي باستخدام Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **الذكاء الاصطناعي الحواري** و**روبوتات الدردشة**. هناك مسار تعلم منفصل [إنشاء حلول الذكاء الاصطناعي الحواري](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum)، ويمكنك أيضًا الرجوع إلى [هذه المقالة](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) لمزيد من التفاصيل.
* **الرياضيات العميقة** وراء التعلم العميق. لهذا، نوصي بكتاب [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) بواسطة Ian Goodfellow، Yoshua Bengio وAaron Courville، وهو متاح أيضًا عبر الإنترنت على [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* **الرياضيات العميقة** وراء التعلم العميق. لهذا، نوصي بكتاب [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) بواسطة Ian Goodfellow، Yoshua Bengio وAaron Courville، المتوفر أيضًا عبر الإنترنت على [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
للحصول على مقدمة لطيفة حول مواضيع _الذكاء الاصطناعي في السحابة_ يمكنك أخذ [البدء مع الذكاء الاصطناعي على Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) مسار التعلم.
@ -75,44 +75,44 @@ CO_OP_TRANSLATOR_METADATA:
| 02 | [تمثيل المعرفة وأنظمة الخبراء](./lessons/2-Symbolic/README.md) | [أنظمة الخبراء](./lessons/2-Symbolic/Animals.ipynb) / [علم الوجود](./lessons/2-Symbolic/FamilyOntology.ipynb) /[مخطط المفاهيم](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**مقدمة إلى الشبكات العصبية**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [بيرسيبترون](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [دفتر الملاحظات](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [مختبر](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [بيرسيبترون متعدد الطبقات وإنشاء إطار العمل الخاص بنا](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [دفتر الملاحظات](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [مختبر](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [مقدمة إلى الأطر (PyTorch/TensorFlow) والإفراط في التعميم](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [مختبر](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| 04 | [بيرسيبترون متعدد الطبقات وإنشاء إطار عمل خاص بنا](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [دفتر الملاحظات](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [مختبر](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [مقدمة إلى الأطر (PyTorch/TensorFlow) والإفراط في التخصيص](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [مختبر](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**الرؤية الحاسوبية**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [استكشاف الرؤية الحاسوبية على Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [مقدمة إلى الرؤية الحاسوبية. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [دفتر ملاحظات](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [مختبر](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [الشبكات العصبية الالتفافية](./lessons/4-ComputerVision/07-ConvNets/README.md) & [هياكل CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [مختبر](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 07 | [الشبكات العصبية الالتفافية](./lessons/4-ComputerVision/07-ConvNets/README.md) & [هياكل الشبكات العصبية الالتفافية](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [مختبر](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [الشبكات المدربة مسبقًا والتعلم بالنقل](./lessons/4-ComputerVision/08-TransferLearning/README.md) و [حيل التدريب](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [مختبر](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [المشفّرات التلقائية و VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [الشبكات التوليدية التنافسية ونقل الأسلوب الفني](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [كشف الأجسام](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [مختبر](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 09 | [المشفرات التلقائية والشبكات التوليدية المتغيرة (VAEs)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [الشبكات التوليدية التنافسية ونقل الأنماط الفنية](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [اكتشاف الكائنات](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [مختبر](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [التجزئة الدلالية. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**معالجة اللغة الطبيعية**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [استكشاف معالجة اللغة الطبيعية على Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [تمثيل النصوص. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [التضمينات الدلالية للكلمات. Word2Vec و GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [نمذجة اللغة. تدريب التضمينات الخاصة بك](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [مختبر](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [الشبكات العصبية المتكررة](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [الشبكات التوليدية المتكررة](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [مختبر](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [المحوّلات. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [التعرف على الكيانات المسماة](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [مختبر](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [نماذج اللغة الكبيرة، برمجة المطالبات والمهام قليلة الأمثلة](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **تقنيات الذكاء الاصطناعي الأخرى** || |
| 13 | [تمثيل النصوص. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [تمثيلات الكلمات الدلالية. Word2Vec و GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [نمذجة اللغة. تدريب تمثيلاتك الخاصة](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [مختبر](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [الشبكات العصبية المتكررة](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [الشبكات التوليدية المتكررة](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [مختبر](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [المحولات. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [التعرف على الكيانات المسماة](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [مختبر](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [النماذج اللغوية الكبيرة، برمجة التوجيه، والمهام قليلة الأمثلة](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **تقنيات أخرى للذكاء الاصطناعي** || |
| 21 | [الخوارزميات الجينية](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [دفتر ملاحظات](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [التعلم العميق المعزز](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [مختبر](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [أنظمة الوكلاء المتعددين](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| 23 | [الأنظمة متعددة الوكلاء](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **أخلاقيات الذكاء الاصطناعي** | | |
| 24 | [أخلاقيات الذكاء الاصطناعي والذكاء الاصطناعي المسؤول](./lessons/7-Ethics/README.md) | [Microsoft Learn: مبادئ الذكاء الاصطناعي المسؤول](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| 24 | [أخلاقيات الذكاء الاصطناعي والذكاء الاصطناعي المسؤول](./lessons/7-Ethics/README.md) | [Microsoft Learn: Responsible AI Principles](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **إضافات** | | |
| 25 | [الشبكات متعددة الوسائط، CLIP و VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [دفتر ملاحظات](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## تحتوي كل درس على
## كل درس يحتوي على
* مواد قراءة مسبقة
* دفاتر ملاحظات Jupyter قابلة للتنفيذ، وغالبًا ما تكون مخصصة للإطار (**PyTorch** أو **TensorFlow**). تحتوي دفاتر الملاحظات القابلة للتنفيذ أيضًا على الكثير من المواد النظرية، لذا لفهم الموضوع، يجب عليك مراجعة نسخة واحدة على الأقل من دفتر الملاحظات (إما PyTorch أو TensorFlow).
* **مختبرات** متوفرة لبعض المواضيع، والتي تمنحك فرصة لتطبيق المواد التي تعلمتها على مشكلة محددة.
* تحتوي بعض الأقسام على روابط إلى [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) التي تغطي مواضيع ذات صلة.
* مواد للقراءة المسبقة
* دفاتر Jupyter قابلة للتنفيذ، وغالبًا ما تكون مخصصة للإطار (**PyTorch** أو **TensorFlow**). تحتوي دفاتر الملاحظات القابلة للتنفيذ أيضًا على الكثير من المواد النظرية، لذا لفهم الموضوع يجب عليك مراجعة نسخة واحدة على الأقل من دفتر الملاحظات (سواء PyTorch أو TensorFlow).
* **مختبرات** متوفرة لبعض المواضيع، والتي تمنحك فرصة لتطبيق ما تعلمته على مشكلة محددة.
* تحتوي بعض الأقسام على روابط إلى وحدات [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) التي تغطي مواضيع ذات صلة.
## البدء
- لقد أنشأنا [درس إعداد](./lessons/0-course-setup/setup.md) لمساعدتك في إعداد بيئة التطوير الخاصة بك. - للمعلمين، قمنا بإنشاء [درس إعداد المناهج](./lessons/0-course-setup/for-teachers.md) لكم أيضًا!
- قمنا بإنشاء [درس إعداد](./lessons/0-course-setup/setup.md) لمساعدتك في إعداد بيئة التطوير الخاصة بك. - للمعلمين، قمنا بإنشاء [درس إعداد المناهج](./lessons/0-course-setup/for-teachers.md) أيضًا!
- كيفية [تشغيل الكود في VSCode أو Codepace](./lessons/0-course-setup/how-to-run.md)
اتبع هذه الخطوات:
@ -121,40 +121,40 @@ CO_OP_TRANSLATOR_METADATA:
قم باستنساخ المستودع: `git clone https://github.com/microsoft/AI-For-Beginners.git`
لا تنسَ وضع نجمة (🌟) لهذا المستودع لتجده بسهولة لاحقًا.
لا تنسَ وضع نجمة (🌟) على هذا المستودع لتسهيل العثور عليه لاحقًا.
## تعرف على متعلمين آخرين
انضم إلى [خادم Discord الرسمي للذكاء الاصطناعي](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) للتواصل مع متعلمين آخرين يأخذون هذا المساق والحصول على الدعم.
انضم إلى [خادم Discord الرسمي للذكاء الاصطناعي](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) للتعرف على متعلمين آخرين يأخذون هذه الدورة والحصول على الدعم.
إذا كان لديك ملاحظات على المنتج أو أسئلة أثناء البناء، قم بزيارة [منتدى مطوري Azure AI Foundry](https://aka.ms/foundry/forum)
إذا كان لديك ملاحظات حول المنتج أو أسئلة أثناء البناء، قم بزيارة [منتدى مطوري Azure AI Foundry](https://aka.ms/foundry/forum)
## الاختبارات
> **ملاحظة حول الاختبارات**: جميع الاختبارات موجودة في مجلد Quiz-app في etc\quiz-app، أو [عبر الإنترنت هنا](https://ff-quizzes.netlify.app/). يتم ربطها من داخل الدروس. يمكن تشغيل تطبيق الاختبارات محليًا أو نشره على Azure؛ اتبع التعليمات الموجودة في مجلد `quiz-app`. يتم ترجمتها تدريجيًا.
> **ملاحظة حول الاختبارات**: جميع الاختبارات موجودة في مجلد Quiz-app داخل etc\quiz-app، أو [عبر الإنترنت هنا](https://ff-quizzes.netlify.app/). يتم الربط بها من داخل الدروس. يمكن تشغيل تطبيق الاختبارات محليًا أو نشره على Azure؛ اتبع التعليمات الموجودة في مجلد `quiz-app`. يتم ترجمتها تدريجيًا.
## مطلوب مساعدة
هل لديك اقتراحات أو وجدت أخطاء إملائية أو في الكود؟ قم بفتح قضية أو إنشاء طلب سحب.
هل لديك اقتراحات أو اكتشفت أخطاء إملائية أو برمجية؟ قم بفتح قضية أو إنشاء طلب سحب.
## شكر خاص
* **✍️ المؤلف الرئيسي:** [دميتري سوشنيكوف](http://soshnikov.com)، دكتوراه
* **🔥 المحررة:** [جين لوبر](https://twitter.com/jenlooper)، دكتوراه
* **🎨 رسامة الرسومات التوضيحية:** [تومومي إيمورا](https://twitter.com/girlie_mac)
* **✅ منشئة الاختبارات:** [لطيفة بيلو](https://github.com/CinnamonXI)، [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 المساهمون الأساسيون:** [إفجيني بيششيك](https://github.com/Pe4enIks)
* **✍️ المؤلف الرئيسي:** [Dmitry Soshnikov](http://soshnikov.com)، دكتوراه
* **🔥 المحرر:** [Jen Looper](https://twitter.com/jenlooper)، دكتوراه
* **🎨 رسام الملاحظات التوضيحية:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ منشئ الاختبارات:** [Lateefah Bello](https://github.com/CinnamonXI)، [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 المساهمون الأساسيون:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## مناهج أخرى
فريقنا ينتج مناهج أخرى! تحقق من:
- [الذكاء الاصطناعي التوليدي للمبتدئين](https://aka.ms/genai-beginners)
- [الذكاء الاصطناعي التوليدي للمبتدئين باستخدام .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [الذكاء الاصطناعي التوليدي للمبتدئين .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [الذكاء الاصطناعي التوليدي باستخدام JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [الذكاء الاصطناعي التوليدي باستخدام Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [الذكاء الاصطناعي للمبتدئين](https://aka.ms/ai-beginners)
- [علم البيانات للمبتدئين](https://aka.ms/datascience-beginners)
- [تعلم الآلة للمبتدئين](https://aka.ms/ml-beginners)
- [الأمن السيبراني للمبتدئين](https://github.com/microsoft/Security-101)
- [الأمن السيبراني للمبتدئين](https://github.com/microsoft/Security-101)
- [تطوير الويب للمبتدئين](https://aka.ms/webdev-beginners)
- [إنترنت الأشياء للمبتدئين](https://aka.ms/iot-beginners)
- [تطوير الواقع الممتد للمبتدئين](https://github.com/microsoft/xr-development-for-beginners)
@ -165,4 +165,4 @@ CO_OP_TRANSLATOR_METADATA:
---
**إخلاء المسؤولية**:
تم ترجمة هذا المستند باستخدام خدمة الترجمة الآلية [Co-op Translator](https://github.com/Azure/co-op-translator). بينما نسعى لتحقيق الدقة، يرجى العلم أن الترجمات الآلية قد تحتوي على أخطاء أو معلومات غير دقيقة. يجب اعتبار المستند الأصلي بلغته الأصلية هو المصدر الموثوق. للحصول على معلومات حساسة أو هامة، يُوصى بالاستعانة بترجمة بشرية احترافية. نحن غير مسؤولين عن أي سوء فهم أو تفسيرات خاطئة ناتجة عن استخدام هذه الترجمة.
تمت ترجمة هذا المستند باستخدام خدمة الترجمة الآلية [Co-op Translator](https://github.com/Azure/co-op-translator). بينما نسعى لتحقيق الدقة، يرجى العلم أن الترجمات الآلية قد تحتوي على أخطاء أو معلومات غير دقيقة. يجب اعتبار المستند الأصلي بلغته الأصلية هو المصدر الموثوق. للحصول على معلومات حساسة أو هامة، يُوصى بالاستعانة بترجمة بشرية احترافية. نحن غير مسؤولين عن أي سوء فهم أو تفسيرات خاطئة تنشأ عن استخدام هذه الترجمة.

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translations/bg/README.md
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@ -1,8 +1,8 @@
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"language_code": "bg"
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@ -21,48 +21,48 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Изкуствен интелект за начинаещи - Учебна програма
# Изкуствен интелект за начинаещи - учебна програма
|![Скица от @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.bg.png)|
|![Скетч от @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.bg.png)|
|:---:|
| Изкуствен интелект за начинаещи - _Скица от [@girlie_mac](https://twitter.com/girlie_mac)_ |
| AI For Beginners - _Скетч от [@girlie_mac](https://twitter.com/girlie_mac)_ |
Изследвайте света на **Изкуствения интелект** (AI) с нашата 12-седмична учебна програма, състояща се от 24 урока! Тя включва практически уроци, тестове и лабораторни упражнения. Програмата е подходяща за начинаещи и обхваща инструменти като TensorFlow и PyTorch, както и етика в AI.
Разгледайте света на **Изкуствения интелект** (AI) с нашата 12-седмична учебна програма, включваща 24 урока! Тя включва практически уроци, тестове и лабораторни упражнения. Програмата е подходяща за начинаещи и обхваща инструменти като TensorFlow и PyTorch, както и етика в AI.
### 🌐 Поддръжка на много езици
#### Поддържано чрез GitHub Action (Автоматизирано и винаги актуално)
[Френски](../fr/README.md) | [Испански](../es/README.md) | [Немски](../de/README.md) | [Руски](../ru/README.md) | [Арабски](../ar/README.md) | [Персийски (Фарси)](../fa/README.md) | [Урду](../ur/README.md) | [Китайски (опростен)](../zh/README.md) | [Китайски (традиционен, Макао)](../mo/README.md) | [Китайски (традиционен, Хонг Конг)](../hk/README.md) | [Китайски (традиционен, Тайван)](../tw/README.md) | [Японски](../ja/README.md) | [Корейски](../ko/README.md) | [Хинди](../hi/README.md) | [Бенгалски](../bn/README.md) | [Марати](../mr/README.md) | [Непалски](../ne/README.md) | [Пенджабски (Гурмукхи)](../pa/README.md) | [Португалски (Португалия)](../pt/README.md) | [Португалски (Бразилия)](../br/README.md) | [Италиански](../it/README.md) | [Полски](../pl/README.md) | [Турски](../tr/README.md) | [Гръцки](../el/README.md) | [Тайландски](../th/README.md) | [Шведски](../sv/README.md) | [Датски](../da/README.md) | [Норвежки](../no/README.md) | [Фински](../fi/README.md) | [Холандски](../nl/README.md) | [Иврит](../he/README.md) | [Виетнамски](../vi/README.md) | [Индонезийски](../id/README.md) | [Малайски](../ms/README.md) | [Тагалог (Филипински)](../tl/README.md) | [Суахили](../sw/README.md) | [Унгарски](../hu/README.md) | [Чешки](../cs/README.md) | [Словашки](../sk/README.md) | [Румънски](../ro/README.md) | [Български](./README.md) | [Сръбски (Кирилица)](../sr/README.md) | [Хърватски](../hr/README.md) | [Словенски](../sl/README.md) | [Украински](../uk/README.md) | [Бирмански (Мианмар)](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](./README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Ако желаете да добавите допълнителни езици, списъкът с поддържаните е наличен [тук](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Ако желаете да добавите допълнителни езици, списъкът с поддържани езици е наличен [тук](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Присъединете се към общността
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Какво ще научите
**[Мисловна карта на курса](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[Майндмап на курса](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
В тази учебна програма ще научите:
* Различни подходи към Изкуствения интелект, включително "добрия стар" символичен подход с **Представяне на знания** и разсъждения ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* Различни подходи към Изкуствения интелект, включително "добрия стар" символичен подход с **Представяне на знания** и разсъждение ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Невронни мрежи** и **Дълбоко обучение**, които са в основата на съвременния AI. Ще илюстрираме концепциите зад тези важни теми с код в две от най-популярните рамки - [TensorFlow](http://Tensorflow.org) и [PyTorch](http://pytorch.org).
* **Невронни архитектури** за работа с изображения и текст. Ще разгледаме съвременни модели, но може да липсват най-новите разработки.
* По-малко популярни подходи в AI, като **Генетични алгоритми** и **Многоагентни системи**.
* **Невронни архитектури** за работа с изображения и текст. Ще разгледаме съвременни модели, но може да липсват някои от най-новите разработки.
* По-малко популярни подходи в AI, като **Генетични алгоритми** и **Системи с множество агенти**.
Какво няма да покрием в тази учебна програма:
> [Намерете всички допълнителни ресурси за този курс в нашата колекция в Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Намерете всички допълнителни ресурси за този курс в нашата колекция Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Бизнес случаи за използване на **AI в бизнеса**. Помислете за преминаване на [Въведение в AI за бизнес потребители](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) или [AI Бизнес училище](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), разработено в сътрудничество с [INSEAD](https://www.insead.edu/).
* Бизнес случаи за използване на **AI в бизнеса**. Помислете за преминаване на [Въведение в AI за бизнес потребители](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) учебен път на Microsoft Learn или [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), разработен в сътрудничество с [INSEAD](https://www.insead.edu/).
* **Класическо машинно обучение**, което е добре описано в нашата [Учебна програма за машинно обучение за начинаещи](http://github.com/Microsoft/ML-for-Beginners).
* Практически AI приложения, изградени с помощта на **[Когнитивни услуги](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. За това препоръчваме да започнете с модулите на Microsoft Learn за [визия](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [обработка на естествен език](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Генеративен AI с Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** и други.
* Специфични ML **облачни рамки**, като [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) или [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Помислете за използване на [Изграждане и управление на решения за машинно обучение с Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) и [Изграждане и управление на решения за машинно обучение с Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Разговорен AI** и **чатботове**. Има отделна [Създаване на решения за разговорен AI](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) учебна пътека, а също така можете да се обърнете към [тази публикация в блога](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) за повече подробности.
* **Дълбока математика** зад дълбокото обучение. За това бихме препоръчали [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) от Ian Goodfellow, Yoshua Bengio и Aaron Courville, която също е достъпна онлайн на [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Практически AI приложения, изградени с **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. За това препоръчваме да започнете с модули Microsoft Learn за [визия](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [обработка на естествен език](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Генеративен AI с Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** и други.
* Специфични ML **Облачни рамки**, като [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) или [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Помислете за използване на [Изграждане и управление на решения за машинно обучение с Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) и [Изграждане и управление на решения за машинно обучение с Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) учебни пътища.
* **Разговорен AI** и **Чат ботове**. Има отделен [Създаване на решения за разговорен AI](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) учебен път, а също така можете да се обърнете към [тази публикация в блога](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) за повече подробности.
* **Дълбока математика** зад дълбокото обучение. За това бихме препоръчали [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) от Ian Goodfellow, Yoshua Bengio и Aaron Courville, която е достъпна онлайн на [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
За леко въведение в темите за _AI в облака_ можете да разгледате [Започнете с изкуствения интелект в Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) учебна пътека.
За леко въведение в темите за _AI в облака_ можете да разгледате [Започнете с изкуствен интелект в Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) учебен път.
# Съдържание
@ -74,60 +74,60 @@ CO_OP_TRANSLATOR_METADATA:
| II | **Символичен AI** |
| 02 | [Представяне на знания и експертни системи](./lessons/2-Symbolic/README.md) | [Експертни системи](./lessons/2-Symbolic/Animals.ipynb) / [Онтология](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Граф на концепции](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Въведение в невронните мрежи**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Перцептрон](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Бележник](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Лаборатория](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Многослойни перцептрони и създаване на собствена рамка](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Бележник](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Лаборатория](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Въведение във фреймуъркове (PyTorch/TensorFlow) и Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лабораторно упражнение](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Компютърно зрение**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Изследване на компютърно зрение в Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Въведение в компютърното зрение. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Бележник](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Лабораторно упражнение](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Конволюционни невронни мрежи](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Архитектури на CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Лабораторно упражнение](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Предварително обучени мрежи и трансферно обучение](./lessons/4-ComputerVision/08-TransferLearning/README.md) и [Трикове за обучение](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лабораторно упражнение](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Автоенкодери и VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 03 | [Перцептрон](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Тетрадка](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Лаборатория](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Многослоен перцептрон и създаване на собствена рамка](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Тетрадка](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Лаборатория](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Въведение в рамките (PyTorch/TensorFlow) и преобучение](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лаборатория](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Компютърно зрение**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Разгледайте компютърното зрение в Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Въведение в компютърното зрение. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Тетрадка](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Лаборатория](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Конволюционни невронни мрежи](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Архитектури на CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Лаборатория](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Предварително обучени мрежи и трансферно обучение](./lessons/4-ComputerVision/08-TransferLearning/README.md) и [Трикове за обучение](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лаборатория](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Автокодери и VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Генеративни състезателни мрежи и трансфер на артистичен стил](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Откриване на обекти](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Лабораторно упражнение](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 11 | [Откриване на обекти](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Лаборатория](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Семантично сегментиране. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Обработка на естествен език**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Изследване на обработката на естествен език в Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Представяне на текст. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Семантични векторни представяния. Word2Vec и GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Моделиране на език. Обучение на собствени векторни представяния](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Лабораторно упражнение](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Рекурентни невронни мрежи](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Генеративни рекурентни мрежи](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Лабораторно упражнение](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Трансформъри. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Разпознаване на именувани обекти](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Лабораторно упражнение](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Големи езикови модели, програмиране с подсказки и задачи с малко примери](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**Обработка на естествен език**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Разгледайте обработката на естествен език в Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Представяне на текст. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Семантични текстови вграждания. Word2Vec и GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Моделиране на език. Обучение на собствени вграждания](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Лаборатория](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Рекурентни невронни мрежи](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Генеративни рекурентни мрежи](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Лаборатория](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Трансформъри. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Разпознаване на именувани обекти](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Лаборатория](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Големи езикови модели, програмиране с подсказки и задачи с малко примери](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Други AI техники** || |
| 21 | [Генетични алгоритми](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Бележник](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Дълбоко обучение чрез подсилване](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Лабораторно упражнение](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Многоагентни системи](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| 21 | [Генетични алгоритми](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Тетрадка](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Дълбоко подсилващо обучение](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Лаборатория](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Системи с множество агенти](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Етика в AI** | | |
| 24 | [Етика в AI и отговорен AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Принципи за отговорен AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Допълнителни материали** | | |
| 25 | [Мултимодални мрежи, CLIP и VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Бележник](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 24 | [Етика в AI и отговорен AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Принципи на отговорния AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Екстри** | | |
| 25 | [Мултимодални мрежи, CLIP и VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Тетрадка](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Всяка лекция съдържа
* Материали за предварително четене
* Изпълними Jupyter бележници, които често са специфични за даден фреймуърк (**PyTorch** или **TensorFlow**). Изпълнимият бележник също съдържа много теоретичен материал, така че за да разберете темата, трябва да преминете поне през една версия на бележника (или PyTorch, или TensorFlow).
* **Лабораторни упражнения**, налични за някои теми, които ви дават възможност да приложите наученото към конкретен проблем.
* Изпълними Jupyter тетрадки, които често са специфични за рамката (**PyTorch** или **TensorFlow**). Изпълнимата тетрадка съдържа и много теоретичен материал, така че за да разберете темата, трябва да преминете поне една версия на тетрадката (PyTorch или TensorFlow).
* **Лаборатории**, налични за някои теми, които ви дават възможност да приложите наученото към конкретен проблем.
* Някои секции съдържат връзки към модули в [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum), които обхващат свързани теми.
## Начало
## Започнете
- Създадохме [лекция за настройка](./lessons/0-course-setup/setup.md), която да ви помогне с настройването на вашата среда за разработка. - За преподаватели създадохме и [лекция за настройка на учебната програма](./lessons/0-course-setup/for-teachers.md)!
- Създадохме [урок за настройка](./lessons/0-course-setup/setup.md), който да ви помогне с настройката на вашата среда за разработка. - За преподаватели създадохме и [урок за настройка на учебна програма](./lessons/0-course-setup/for-teachers.md)!
- Как да [стартирате кода във VSCode или Codepace](./lessons/0-course-setup/how-to-run.md)
Следвайте тези стъпки:
Форкнете репозитория: Кликнете върху бутона "Fork" в горния десен ъгъл на тази страница.
Форкнете хранилището: Кликнете върху бутона "Fork" в горния десен ъгъл на тази страница.
Клонирайте репозитория: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Клонирайте хранилището: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Не забравяйте да добавите звезда (🌟) на този репо, за да го намерите по-лесно по-късно.
Не забравяйте да дадете звезда (🌟) на това хранилище, за да го намерите по-лесно по-късно.
## Срещнете други обучаващи се
## Запознайте се с други обучаващи се
Присъединете се към нашия [официален AI Discord сървър](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), за да се срещнете и свържете с други обучаващи се, които преминават този курс, и да получите подкрепа.
Ако имате обратна връзка за продукта или въпроси по време на изграждането, посетете нашия [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
Ако имате обратна връзка за продукта или въпроси по време на разработката, посетете нашия [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Тестове
> **Бележка относно тестовете**: Всички тестове се намират в папката Quiz-app в etc\quiz-app, или [Онлайн тук](https://ff-quizzes.netlify.app/). Те са свързани с уроците, като приложението за тестове може да бъде стартирано локално или разположено в Azure; следвайте инструкциите в папката `quiz-app`. Те постепенно се локализират.
@ -137,32 +137,32 @@ CO_OP_TRANSLATOR_METADATA:
## Специални благодарности
* **✍️ Основен автор:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Редактор:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Илюстратор на скици:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Създател на тестове:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Основни сътрудници:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ Основен автор:** [Дмитрий Сошников](http://soshnikov.com), доктор на науките
* **🔥 Редактор:** [Джен Лупър](https://twitter.com/jenlooper), доктор на науките
* **🎨 Илюстратор на скици:** [Томоми Имура](https://twitter.com/girlie_mac)
* **✅ Създател на тестове:** [Латифа Бело](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Основни сътрудници:** [Евгений Пищик](https://github.com/Pe4enIks)
## Други учебни материали
## Други учебни програми
Нашият екип създава и други учебни материали! Вижте:
Нашият екип създава и други учебни програми! Разгледайте:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
- [Генеративен AI за начинаещи](https://aka.ms/genai-beginners)
- [Генеративен AI за начинаещи .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Генеративен AI с JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Генеративен AI с Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI за начинаещи](https://aka.ms/ai-beginners)
- [Наука за данни за начинаещи](https://aka.ms/datascience-beginners)
- [Машинно обучение за начинаещи](https://aka.ms/ml-beginners)
- [Киберсигурност за начинаещи](https://github.com/microsoft/Security-101)
- [Уеб разработка за начинаещи](https://aka.ms/webdev-beginners)
- [IoT за начинаещи](https://aka.ms/iot-beginners)
- [XR разработка за начинаещи](https://github.com/microsoft/xr-development-for-beginners)
- [Овладяване на GitHub Copilot за агентно използване](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Овладяване на GitHub Copilot за C#/.NET разработчици](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Избери своето приключение с Copilot](https://github.com/microsoft/CopilotAdventures)
---
**Отказ от отговорност**:
Този документ е преведен с помощта на AI услуга за превод [Co-op Translator](https://github.com/Azure/co-op-translator). Въпреки че се стремим към точност, моля, имайте предвид, че автоматичните преводи може да съдържат грешки или неточности. Оригиналният документ на неговия изходен език трябва да се счита за авторитетен източник. За критична информация се препоръчва професионален превод от човек. Ние не носим отговорност за каквито и да е недоразумения или погрешни интерпретации, произтичащи от използването на този превод.
Този документ е преведен с помощта на AI услуга за превод [Co-op Translator](https://github.com/Azure/co-op-translator). Въпреки че се стремим към точност, моля, имайте предвид, че автоматизираните преводи може да съдържат грешки или неточности. Оригиналният документ на неговия роден език трябва да се счита за авторитетен източник. За критична информация се препоръчва професионален човешки превод. Не носим отговорност за недоразумения или погрешни интерпретации, произтичащи от използването на този превод.

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@ -21,21 +21,21 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# কৃত্রিম বুদ্ধিমত্তা শিক্ষার জন্য প্রাথমিক পাঠক্রম
# শিক্ষার্থীদের জন্য কৃত্রিম বুদ্ধিমত্তা - একটি পাঠ্যক্রম
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.bn.png)|
|:---:|
| কৃত্রিম বুদ্ধিমত্তা শিক্ষার জন্য প্রাথমিক পাঠক্রম - _স্কেচনোট [@girlie_mac](https://twitter.com/girlie_mac)_ |
| শিক্ষার্থীদের জন্য কৃত্রিম বুদ্ধিমত্তা - _স্কেচনোট [@girlie_mac](https://twitter.com/girlie_mac)_ |
**কৃত্রিম বুদ্ধিমত্তা** (AI)-এর জগৎ আবিষ্কার করুন আমাদের ১২-সপ্তাহের, ২৪-টি পাঠের পাঠক্রমের মাধ্যমে! এতে রয়েছে ব্যবহারিক পাঠ, কুইজ এবং ল্যাব। এই পাঠক্রমটি নতুনদের জন্য উপযোগী এবং এতে TensorFlow এবং PyTorch-এর মতো টুলস এবং AI-এর নৈতিকতা অন্তর্ভুক্ত।
**কৃত্রিম বুদ্ধিমত্তা** (AI)-এর জগৎ আবিষ্কার করুন আমাদের ১২-সপ্তাহ, ২৪-লেসনের পাঠ্যক্রমের মাধ্যমে! এতে রয়েছে ব্যবহারিক পাঠ, কুইজ এবং ল্যাব। এই পাঠ্যক্রমটি শিক্ষার্থীদের জন্য সহজবোধ্য এবং এতে TensorFlow এবং PyTorch-এর মতো টুলস, পাশাপাশি AI-এর নৈতিকতা অন্তর্ভুক্ত রয়েছে।
### 🌐 বহু-ভাষা সমর্থন
### 🌐 বহু-ভাষার সমর্থন
#### GitHub Action-এর মাধ্যমে সমর্থিত (স্বয়ংক্রিয় এবং সর্বদা আপডেটেড)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](./README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**যদি আপনি অতিরিক্ত ভাষার অনুবাদ চান, তাহলে [এখানে](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) তালিকাভুক্ত ভাষাগুলি দেখুন।**
**যদি আপনি অতিরিক্ত ভাষার অনুবাদ চান, সমর্থিত ভাষার তালিকা [এখানে](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) পাওয়া যাবে।**
## কমিউনিটিতে যোগ দিন
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -44,25 +44,25 @@ CO_OP_TRANSLATOR_METADATA:
**[কোর্সের মানচিত্র](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
এই পাঠক্রমে আপনি শিখবেন:
এই পাঠ্যক্রমে আপনি শিখবেন:
* কৃত্রিম বুদ্ধিমত্তার বিভিন্ন পদ্ধতি, যার মধ্যে রয়েছে "পুরনো দিনের" প্রতীকী পদ্ধতি **জ্ঞান উপস্থাপনা** এবং যুক্তি ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))।
* **নিউরাল নেটওয়ার্ক** এবং **ডিপ লার্নিং**, যা আধুনিক AI-এর মূল ভিত্তি। আমরা এই গুরুত্বপূর্ণ বিষয়গুলির ধারণাগুলি ব্যাখ্যা করব দুটি জনপ্রিয় ফ্রেমওয়ার্ক - [TensorFlow](http://Tensorflow.org) এবং [PyTorch](http://pytorch.org)-এর কোড ব্যবহার করে।
* চিত্র এবং টেক্সট নিয়ে কাজ করার জন্য **নিউরাল আর্কিটেকচার**। আমরা সাম্প্রতিক মডেলগুলি কভার করব, তবে সর্বশেষ প্রযুক্তি সম্পর্কে কিছুটা কম থাকতে পারে।
* কৃত্রিম বুদ্ধিমত্তার বিভিন্ন পদ্ধতি, যার মধ্যে রয়েছে "পুরনো ভালো" প্রতীকী পদ্ধতি **জ্ঞান উপস্থাপনা** এবং যুক্তি ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))।
* **নিউরাল নেটওয়ার্ক** এবং **ডিপ লার্নিং**, যা আধুনিক AI-এর মূল। আমরা এই গুরুত্বপূর্ণ বিষয়গুলির ধারণাগুলি দুটি জনপ্রিয় ফ্রেমওয়ার্ক - [TensorFlow](http://Tensorflow.org) এবং [PyTorch](http://pytorch.org)-এ কোড ব্যবহার করে ব্যাখ্যা করব।
* **নিউরাল আর্কিটেকচার** চিত্র এবং টেক্সট নিয়ে কাজ করার জন্য। আমরা সাম্প্রতিক মডেলগুলি কভার করব তবে কিছু ক্ষেত্রে সর্বাধুনিক প্রযুক্তি অনুপস্থিত থাকতে পারে।
* কম জনপ্রিয় AI পদ্ধতি, যেমন **জেনেটিক অ্যালগরিদম** এবং **মাল্টি-এজেন্ট সিস্টেম**।
এই পাঠক্রমে যা অন্তর্ভুক্ত নয়:
এই পাঠ্যক্রমে যা অন্তর্ভুক্ত করা হবে না:
> [এই কোর্সের জন্য সমস্ত অতিরিক্ত সম্পদ Microsoft Learn সংগ্রহে খুঁজুন](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **ব্যবসায়িক ক্ষেত্রে AI-এর ব্যবহার**। Microsoft Learn-এ [ব্যবসায়িক ব্যবহারকারীদের জন্য AI পরিচিতি](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ বা [AI ব্যবসায়িক স্কুল](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), যা [INSEAD](https://www.insead.edu/)-এর সহযোগিতায় তৈরি করা হয়েছে, গ্রহণ করার কথা বিবেচনা করুন।
* **ক্লাসিক মেশিন লার্নিং**, যা আমাদের [মেশিন লার্নিং শিক্ষার জন্য প্রাথমিক পাঠক্রম](http://github.com/Microsoft/ML-for-Beginners)-এ ভালোভাবে বর্ণনা করা হয়েছে।
* **[কগনিটিভ সার্ভিসেস](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** ব্যবহার করে তৈরি করা ব্যবহারিক AI অ্যাপ্লিকেশন। এর জন্য, আমরা Microsoft Learn-এর [ভিশন](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [ন্যাচারাল ল্যাঙ্গুয়েজ প্রসেসিং](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI সার্ভিসের সাথে জেনারেটিভ AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** এবং অন্যান্য মডিউল দিয়ে শুরু করার পরামর্শ দিই।
* নির্দিষ্ট ML **ক্লাউড ফ্রেমওয়ার্ক**, যেমন [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), বা [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)। [Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) এবং [Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ ব্যবহার করার কথা বিবেচনা করুন।
* **কথোপকথনমূলক AI** এবং **চ্যাট বট**। এর জন্য একটি আলাদা [কথোপকথনমূলক AI সমাধান তৈরি করুন](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ রয়েছে, এবং আরও বিশদ জানতে [এই ব্লগ পোস্টটি](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) দেখুন।
* **ডিপ লার্নিং-এর গভীর গণিত**। এর জন্য, আমরা Ian Goodfellow, Yoshua Bengio এবং Aaron Courville-এর [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) বইটি সুপারিশ করি, যা অনলাইনে [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) এও পাওয়া যায়।
* **ব্যবসায়িক ক্ষেত্রে AI-এর ব্যবহার**। [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) লার্নিং পাথ বা [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), যা [INSEAD](https://www.insead.edu/) এর সহযোগিতায় তৈরি করা হয়েছে, গ্রহণ করার পরামর্শ দেওয়া হয়।
* **ক্লাসিক মেশিন লার্নিং**, যা আমাদের [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners)-এ ভালোভাবে বর্ণনা করা হয়েছে।
* **কগনিটিভ সার্ভিসেস** ব্যবহার করে তৈরি করা ব্যবহারিক AI অ্যাপ্লিকেশন। এর জন্য, আমরা Microsoft Learn-এর মডিউলগুলি শুরু করার পরামর্শ দিই যেমন [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** এবং অন্যান্য।
* নির্দিষ্ট ML **ক্লাউড ফ্রেমওয়ার্ক**, যেমন [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), বা [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)। [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) এবং [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) লার্নিং পাথ গ্রহণ করার পরামর্শ দেওয়া হয়।
* **কনভারসেশনাল AI** এবং **চ্যাট বট**। এর জন্য একটি পৃথক [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) লার্নিং পাথ রয়েছে, এবং আরও বিস্তারিত জানার জন্য [এই ব্লগ পোস্ট](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) দেখুন।
* **ডিপ ম্যাথমেটিক্স** যা ডিপ লার্নিংয়ের পেছনে রয়েছে। এর জন্য, আমরা Ian Goodfellow, Yoshua Bengio এবং Aaron Courville-এর [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) বইটি সুপারিশ করি, যা অনলাইনে [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) এও উপলব্ধ।
_ক্লাউডে AI-এর_ বিষয়গুলির একটি সহজ পরিচিতির জন্য, আপনি [Azure-এ কৃত্রিম বুদ্ধিমত্তার সাথে শুরু করুন](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ গ্রহণ করতে পারেন।
ক্লাউডে _AI_-এর একটি সহজ ভূমিকা পেতে আপনি [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) লার্নিং পাথ গ্রহণ করতে পারেন।
# বিষয়বস্তু
@ -72,28 +72,28 @@ _ক্লাউডে AI-এর_ বিষয়গুলির একটি
| I | [**AI-এর পরিচিতি**](./lessons/1-Intro/README.md) | | |
| 01 | [AI-এর পরিচিতি এবং ইতিহাস](./lessons/1-Intro/README.md) | - | - |
| II | **প্রতীকী AI** |
| 02 | [জ্ঞান উপস্থাপনা এবং বিশেষজ্ঞ সিস্টেম](./lessons/2-Symbolic/README.md) | [বিশেষজ্ঞ সিস্টেম](./lessons/2-Symbolic/Animals.ipynb) / [অন্তর্ভুক্তি](./lessons/2-Symbolic/FamilyOntology.ipynb) /[ধারণা গ্রাফ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| 02 | [জ্ঞান উপস্থাপনা এবং বিশেষজ্ঞ সিস্টেম](./lessons/2-Symbolic/README.md) | [বিশেষজ্ঞ সিস্টেম](./lessons/2-Symbolic/Animals.ipynb) / [অন্টোলজি](./lessons/2-Symbolic/FamilyOntology.ipynb) /[কনসেপ্ট গ্রাফ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**নিউরাল নেটওয়ার্কের পরিচিতি**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [পারসেপট্রন](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [নোটবুক](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [ল্যাব](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [মাল্টি-লেয়ার পারসেপট্রন এবং আমাদের নিজস্ব ফ্রেমওয়ার্ক তৈরি করা](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [নোটবুক](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [ল্যাব](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [ফ্রেমওয়ার্ক (PyTorch/TensorFlow) এবং ওভারফিটিং এর পরিচিতি](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [ল্যাব](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| 05 | [ফ্রেমওয়ার্কের পরিচিতি (PyTorch/TensorFlow) এবং ওভারফিটিং](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [ল্যাব](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**কম্পিউটার ভিশন**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure-এ কম্পিউটার ভিশন অন্বেষণ করুন](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [কম্পিউটার ভিশনের পরিচিতি। OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [নোটবুক](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [ল্যাব](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [কনভলিউশনাল নিউরাল নেটওয়ার্ক](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN আর্কিটেকচার](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [ল্যাব](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 07 | [কনভোলিউশনাল নিউরাল নেটওয়ার্ক](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN আর্কিটেকচার](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [ল্যাব](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [প্রি-ট্রেইনড নেটওয়ার্ক এবং ট্রান্সফার লার্নিং](./lessons/4-ComputerVision/08-TransferLearning/README.md) এবং [ট্রেনিং ট্রিকস](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [ল্যাব](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [অটোএনকোডার এবং VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [জেনারেটিভ অ্যাডভার্সারিয়াল নেটওয়ার্ক এবং আর্টিস্টিক স্টাইল ট্রান্সফার](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [অবজেক্ট ডিটেকশন](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [ল্যাব](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [সেমান্টিক সেগমেন্টেশন। U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**ন্যাচারাল ল্যাঙ্গুয়েজ প্রসেসিং**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure-এ ন্যাচারাল ল্যাঙ্গুয়েজ প্রসেসিং অন্বেষণ করুন](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [টেক্সট রিপ্রেজেন্টেশন। Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [সেমান্টিক ওয়ার্ড এমবেডিং। Word2Vec এবং GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [ল্যাঙ্গুয়েজ মডেলিং। নিজের এমবেডিং ট্রেনিং করুন](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [ল্যাব](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [রিকারেন্ট নিউরাল নেটওয়ার্ক](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [জেনারেটিভ রিকারেন্ট নেটওয়ার্ক](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [ল্যাব](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ট্রান্সফর্মার। BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [নেমড এন্টিটি রিকগনিশন](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [ল্যাব](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [বড় ল্যাঙ্গুয়েজ মডেল, প্রম্পট প্রোগ্রামিং এবং ফিউ-শট টাস্ক](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [টেক্সট রিপ্রেজেন্টেশন। Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [সেমান্টিক ওয়ার্ড এমবেডিং। Word2Vec এবং GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [ল্যাঙ্গুয়েজ মডেলিং। নিজের এমবেডিং ট্রেনিং করুন](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [ল্যাব](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [রিকারেন্ট নিউরাল নেটওয়ার্ক](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [জেনারেটিভ রিকারেন্ট নেটওয়ার্ক](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [ল্যাব](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ট্রান্সফর্মার। BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [নেমড এন্টিটি রিকগনিশন](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [ল্যাব](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [বড় ল্যাঙ্গুয়েজ মডেল, প্রম্পট প্রোগ্রামিং এবং ফিউ-শট টাস্ক](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **অন্যান্য AI কৌশল** || |
| 21 | [জেনেটিক অ্যালগরিদম](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [নোটবুক](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [ডিপ রিইনফোর্সমেন্ট লার্নিং](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [ল্যাব](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -101,18 +101,18 @@ _ক্লাউডে AI-এর_ বিষয়গুলির একটি
| VII | **AI নৈতিকতা** | | |
| 24 | [AI নৈতিকতা এবং দায়িত্বশীল AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: দায়িত্বশীল AI নীতিমালা](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **অতিরিক্ত বিষয়** | | |
| 25 | [মাল্টি-মোডাল নেটওয়ার্ক, CLIP এবং VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [নোটবুক](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 25 | [মাল্টি-মডাল নেটওয়ার্ক, CLIP এবং VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [নোটবুক](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## প্রতিটি পাঠে অন্তর্ভুক্ত
## প্রতিটি পাঠে অন্তর্ভুক্ত রয়েছে
* প্রি-রিডিং উপকরণ
* এক্সিকিউটেবল Jupyter নোটবুক, যা প্রায়ই ফ্রেমওয়ার্ক (**PyTorch** বা **TensorFlow**) অনুযায়ী নির্দিষ্ট। এক্সিকিউটেবল নোটবুকে প্রচুর তাত্ত্বিক উপকরণও থাকে, তাই বিষয়টি বুঝতে হলে আপনাকে অন্তত একটি সংস্করণ (PyTorch বা TensorFlow) পড়তে হবে।
* এক্সিকিউটেবল Jupyter নোটবুক, যা প্রায়ই ফ্রেমওয়ার্ক (**PyTorch** বা **TensorFlow**) অনুযায়ী নির্দিষ্ট। এক্সিকিউটেবল নোটবুকে প্রচুর তাত্ত্বিক উপকরণও রয়েছে, তাই বিষয়টি বুঝতে হলে আপনাকে অন্তত একটি সংস্করণ (PyTorch বা TensorFlow) পড়তে হবে।
* **ল্যাব** কিছু বিষয়ে উপলব্ধ, যা আপনাকে শিখানো উপকরণ একটি নির্দিষ্ট সমস্যায় প্রয়োগ করার সুযোগ দেয়।
* কিছু বিভাগে [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) মডিউলের লিঙ্ক রয়েছে যা সম্পর্কিত বিষয়গুলি কভার করে।
## শুরু করা
## শুরু করার জন্য
- আমরা একটি [সেটআপ পাঠ](./lessons/0-course-setup/setup.md) তৈরি করেছি যা আপনার ডেভেলপমেন্ট পরিবেশ সেটআপে সাহায্য করবে। - শিক্ষকদের জন্য, আমরা একটি [কারিকুলাম সেটআপ পাঠ](./lessons/0-course-setup/for-teachers.md) তৈরি করেছি!
- আমরা একটি [সেটআপ পাঠ](./lessons/0-course-setup/setup.md) তৈরি করেছি যা আপনার ডেভেলপমেন্ট পরিবেশ সেটআপে সাহায্য করবে। - শিক্ষকদের জন্য, আমরা একটি [কারিকুলা সেটআপ পাঠ](./lessons/0-course-setup/for-teachers.md) তৈরি করেছি!
- কিভাবে [VSCode বা Codepace-এ কোড চালাবেন](./lessons/0-course-setup/how-to-run.md)
এই ধাপগুলি অনুসরণ করুন:
@ -121,7 +121,7 @@ _ক্লাউডে AI-এর_ বিষয়গুলির একটি
রিপোজিটরি ক্লোন করুন: `git clone https://github.com/microsoft/AI-For-Beginners.git`
এই রিপোজিটরিকে সহজে খুঁজে পেতে 🌟 দিয়ে চিহ্নিত করতে ভুলবেন না।
এই রিপোজিটরিকে সহজে খুঁজে পেতে পরে এটি স্টার (🌟) দিতে ভুলবেন না।
## অন্যান্য শিক্ষার্থীদের সাথে পরিচিত হন
@ -130,39 +130,39 @@ _ক্লাউডে AI-এর_ বিষয়গুলির একটি
যদি আপনার পণ্য সম্পর্কিত মতামত বা প্রশ্ন থাকে, আমাদের [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)-এ যান।
## কুইজ
> **কুইজ সম্পর্কে একটি নোট**: সমস্ত কুইজ `etc\quiz-app`-এর Quiz-app ফোল্ডারে সংরক্ষিত আছে, অথবা [অনলাইনে এখানে](https://ff-quizzes.netlify.app/) পাওয়া যাবে। এগুলো পাঠের মধ্যে থেকে লিঙ্ক করা হয়েছে। কুইজ অ্যাপটি স্থানীয়ভাবে চালানো বা Azure-এ ডিপ্লয় করা যেতে পারে; `quiz-app` ফোল্ডারে দেওয়া নির্দেশনা অনুসরণ করুন। এগুলো ধীরে ধীরে স্থানীয় ভাষায় অনুবাদ করা হচ্ছে।
## সাহায্যের প্রয়োজন
> **কুইজ সম্পর্কে একটি নোট**: সমস্ত কুইজ `etc\quiz-app`-এর Quiz-app ফোল্ডারে সংরক্ষিত আছে, অথবা [অনলাইনে এখানে](https://ff-quizzes.netlify.app/) পাওয়া যাবে। এগুলো পাঠের মধ্যে থেকে লিঙ্ক করা হয়েছে। কুইজ অ্যাপটি লোকালভাবে চালানো বা Azure-এ ডিপ্লয় করা যেতে পারে; `quiz-app` ফোল্ডারে দেওয়া নির্দেশনা অনুসরণ করুন। এগুলো ধীরে ধীরে লোকালাইজ করা হচ্ছে।
## সাহায্য প্রয়োজন
আপনার কি কোনো পরামর্শ আছে বা বানান বা কোডের ভুল খুঁজে পেয়েছেন? একটি ইস্যু উত্থাপন করুন বা একটি পুল রিকোয়েস্ট তৈরি করুন।
আপনার কি কোনো পরামর্শ আছে বা বানান বা কোডের ভুল খুঁজে পেয়েছেন? একটি ইস্যু তুলুন বা একটি পুল রিকোয়েস্ট তৈরি করুন।
## বিশেষ ধন্যবাদ
* **✍️ প্রধান লেখক:** [Dmitry Soshnikov](http://soshnikov.com), পিএইচডি
* **🔥 সম্পাদক:** [Jen Looper](https://twitter.com/jenlooper), পিএইচডি
* **✍️ প্রধান লেখক:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 সম্পাদক:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 স্কেচনোট ইলাস্ট্রেটর:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ কুইজ নির্মাতা:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 মূল অবদানকারী:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## অন্যান্য পাঠক্রম
## অন্যান্য পাঠ্যক্রম
আমাদের দল অন্যান্য পাঠক্রমও তৈরি করে! দেখে নিন:
আমাদের টিম অন্যান্য পাঠ্যক্রমও তৈরি করে! দেখুন:
- [শুরুদের জন্য জেনারেটিভ এআই](https://aka.ms/genai-beginners)
- [শুরুদের জন্য জেনারেটিভ এআই .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [জাভাস্ক্রিপ্ট দিয়ে জেনারেটিভ এআই](https://github.com/microsoft/generative-ai-with-javascript)
- [জাভা দিয়ে জেনারেটিভ এআই](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [শুরুদের জন্য এআই](https://aka.ms/ai-beginners)
- [শুরুদের জন্য ডেটা সায়েন্স](https://aka.ms/datascience-beginners)
- [শুরুদের জন্য মেশিন লার্নিং](https://aka.ms/ml-beginners)
- [শুরুদের জন্য সাইবারসিকিউরিটি](https://github.com/microsoft/Security-101)
- [শুরুদের জন্য ওয়েব ডেভেলপমেন্ট](https://aka.ms/webdev-beginners)
- [শুরুদের জন্য IoT](https://aka.ms/iot-beginners)
- [শুরুদের জন্য XR ডেভেলপমেন্ট](https://github.com/microsoft/xr-development-for-beginners)
- [এজেন্টিক ব্যবহারের জন্য GitHub Copilot আয়ত্ত করা](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [C#/.NET ডেভেলপারদের জন্য GitHub Copilot আয়ত্ত করা](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [আপনার নিজস্ব Copilot অ্যাডভেঞ্চার বেছে নিন](https://github.com/microsoft/CopilotAdventures)
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---
**অস্বীকৃতি**:
এই নথিটি AI অনুবাদ পরিষেবা [Co-op Translator](https://github.com/Azure/co-op-translator) ব্যবহার করে অনুবাদ করা হয়েছে। আমরা যথাসম্ভব সঠিক অনুবাদের চেষ্টা করি, তবে অনুগ্রহ করে মনে রাখবেন যে স্বয়ংক্রিয় অনুবাদে ত্রুটি বা অসঙ্গতি থাকতে পারে। নথিটির মূল ভাষায় লেখা সংস্করণটিকেই প্রামাণিক উৎস হিসেবে বিবেচনা করা উচিত। গুরুত্বপূর্ণ তথ্যের জন্য, পেশাদার মানব অনুবাদ ব্যবহার করার পরামর্শ দেওয়া হয়। এই অনুবাদ ব্যবহারের ফলে সৃষ্ট কোনো ভুল বোঝাবুঝি বা ভুল ব্যাখ্যার জন্য আমরা দায়ী নই।
এই নথিটি AI অনুবাদ পরিষেবা [Co-op Translator](https://github.com/Azure/co-op-translator) ব্যবহার করে অনুবাদ করা হয়েছে। আমরা যথাসম্ভব সঠিক অনুবাদের চেষ্টা করি, তবে অনুগ্রহ করে মনে রাখবেন যে স্বয়ংক্রিয় অনুবাদে ত্রুটি বা অসঙ্গতি থাকতে পারে। নথিটির মূল ভাষায় লেখা সংস্করণটিকেই প্রামাণিক উৎস হিসেবে বিবেচনা করা উচিত। গুরুত্বপূর্ণ তথ্যের জন্য, পেশাদার মানব অনুবাদ ব্যবহার করার পরামর্শ দেওয়া হচ্ছে। এই অনুবাদ ব্যবহারের ফলে সৃষ্ট কোনো ভুল বোঝাবুঝি বা ভুল ব্যাখ্যার জন্য আমরা দায়ী নই।

88
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@ -1,8 +1,8 @@
<!--
CO_OP_TRANSLATOR_METADATA:
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"original_hash": "07191303b7ea2aff1d47e2b0fe4bb862",
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"translation_date": "2025-09-07T13:45:35+00:00",
"source_file": "README.md",
"language_code": "br"
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@ -25,41 +25,41 @@ CO_OP_TRANSLATOR_METADATA:
|![Sketchnote por @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.br.png)|
|:---:|
| AI para Iniciantes - _Sketchnote por [@girlie_mac](https://twitter.com/girlie_mac)_ |
| AI For Beginners - _Sketchnote por [@girlie_mac](https://twitter.com/girlie_mac)_ |
Explore o mundo da **Inteligência Artificial** (IA) com nosso currículo de 12 semanas e 24 aulas! Ele inclui lições práticas, questionários e laboratórios. O currículo é amigável para iniciantes e aborda ferramentas como TensorFlow e PyTorch, além de ética em IA.
Explore o mundo da **Inteligência Artificial** (IA) com nosso currículo de 12 semanas e 24 aulas! Ele inclui lições práticas, quizzes e laboratórios. O currículo é voltado para iniciantes e aborda ferramentas como TensorFlow e PyTorch, além de ética na IA.
### 🌐 Suporte Multilíngue
#### Suportado via GitHub Action (Automatizado e Sempre Atualizado)
[Francês](../fr/README.md) | [Espanhol](../es/README.md) | [Alemão](../de/README.md) | [Russo](../ru/README.md) | [Árabe](../ar/README.md) | [Persa (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinês (Simplificado)](../zh/README.md) | [Chinês (Tradicional, Macau)](../mo/README.md) | [Chinês (Tradicional, Hong Kong)](../hk/README.md) | [Chinês (Tradicional, Taiwan)](../tw/README.md) | [Japonês](../ja/README.md) | [Coreano](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Português (Portugal)](../pt/README.md) | [Português (Brasil)](./README.md) | [Italiano](../it/README.md) | [Polonês](../pl/README.md) | [Turco](../tr/README.md) | [Grego](../el/README.md) | [Tailandês](../th/README.md) | [Sueco](../sv/README.md) | [Dinamarquês](../da/README.md) | [Norueguês](../no/README.md) | [Finlandês](../fi/README.md) | [Holandês](../nl/README.md) | [Hebraico](../he/README.md) | [Vietnamita](../vi/README.md) | [Indonésio](../id/README.md) | [Malaio](../ms/README.md) | [Tagalo (Filipino)](../tl/README.md) | [Suaíli](../sw/README.md) | [Húngaro](../hu/README.md) | [Tcheco](../cs/README.md) | [Eslovaco](../sk/README.md) | [Romeno](../ro/README.md) | [Búlgaro](../bg/README.md) | [Sérvio (Cirílico)](../sr/README.md) | [Croata](../hr/README.md) | [Esloveno](../sl/README.md) | [Ucraniano](../uk/README.md) | [Birmanês (Myanmar)](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](./README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Se você deseja ter suporte para idiomas adicionais, eles estão listados [aqui](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Se você deseja ter suporte para idiomas adicionais, os idiomas suportados estão listados [aqui](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Junte-se à Comunidade
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## O que você vai aprender
**[Mapa Mental do Curso](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[Mapa mental do curso](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
Neste currículo, você aprenderá:
* Diferentes abordagens para Inteligência Artificial, incluindo a abordagem simbólica "clássica" com **Representação de Conhecimento** e raciocínio ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Redes Neurais** e **Aprendizado Profundo**, que estão no centro da IA moderna. Vamos ilustrar os conceitos por trás desses tópicos importantes usando código em dois dos frameworks mais populares - [TensorFlow](http://Tensorflow.org) e [PyTorch](http://pytorch.org).
* **Arquiteturas Neurais** para trabalhar com imagens e texto. Vamos abordar modelos recentes, mas talvez não os mais avançados.
* Diferentes abordagens para Inteligência Artificial, incluindo a abordagem simbólica "tradicional" com **Representação de Conhecimento** e raciocínio ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Redes Neurais** e **Aprendizado Profundo**, que estão no núcleo da IA moderna. Vamos ilustrar os conceitos por trás desses tópicos importantes usando código em dois dos frameworks mais populares - [TensorFlow](http://Tensorflow.org) e [PyTorch](http://pytorch.org).
* **Arquiteturas Neurais** para trabalhar com imagens e texto. Vamos abordar modelos recentes, mas talvez faltem alguns dos mais avançados.
* Abordagens menos populares de IA, como **Algoritmos Genéticos** e **Sistemas Multiagentes**.
O que não será abordado neste currículo:
> [Encontre todos os recursos adicionais para este curso em nossa coleção no Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Casos de uso de **IA nos Negócios**. Considere fazer o caminho de aprendizado [Introdução à IA para usuários de negócios](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) no Microsoft Learn, ou a [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), desenvolvida em cooperação com a [INSEAD](https://www.insead.edu/).
* Casos de uso de **IA em Negócios**. Considere fazer o caminho de aprendizado [Introdução à IA para usuários de negócios](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) no Microsoft Learn, ou [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), desenvolvido em cooperação com [INSEAD](https://www.insead.edu/).
* **Aprendizado de Máquina Clássico**, que está bem descrito em nosso [Currículo de Aprendizado de Máquina para Iniciantes](http://github.com/Microsoft/ML-for-Beginners).
* Aplicações práticas de IA construídas usando **[Serviços Cognitivos](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Para isso, recomendamos começar com os módulos do Microsoft Learn para [visão](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [processamento de linguagem natural](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[IA Generativa com o Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** e outros.
* Frameworks específicos de ML **na Nuvem**, como [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) ou [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Considere usar os caminhos de aprendizado [Crie e opere soluções de aprendizado de máquina com o Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) e [Crie e opere soluções de aprendizado de máquina com o Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **IA Conversacional** e **Chatbots**. Há um caminho de aprendizado separado [Crie soluções de IA conversacional](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), e você também pode consultar [este post no blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) para mais detalhes.
* Aplicações práticas de IA construídas usando **[Serviços Cognitivos](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Para isso, recomendamos começar com os módulos do Microsoft Learn para [visão](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [processamento de linguagem natural](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[IA Generativa com Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** e outros.
* Frameworks específicos de **Aprendizado de Máquina na Nuvem**, como [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), ou [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Considere usar os caminhos de aprendizado [Construa e opere soluções de aprendizado de máquina com Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) e [Construa e opere soluções de aprendizado de máquina com Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **IA Conversacional** e **Chat Bots**. Há um caminho de aprendizado separado [Crie soluções de IA conversacional](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), e você também pode consultar [este post no blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) para mais detalhes.
* **Matemática Avançada** por trás do aprendizado profundo. Para isso, recomendamos [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) de Ian Goodfellow, Yoshua Bengio e Aaron Courville, que também está disponível online em [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Para uma introdução mais leve aos tópicos de _IA na Nuvem_, você pode considerar fazer o caminho de aprendizado [Introdução à inteligência artificial no Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
@ -72,28 +72,28 @@ Para uma introdução mais leve aos tópicos de _IA na Nuvem_, você pode consid
| I | [**Introdução à IA**](./lessons/1-Intro/README.md) | | |
| 01 | [Introdução e História da IA](./lessons/1-Intro/README.md) | - | - |
| II | **IA Simbólica** |
| 02 | [Representação de Conhecimento e Sistemas Especialistas](./lessons/2-Symbolic/README.md) | [Sistemas Especialistas](./lessons/2-Symbolic/Animals.ipynb) / [Ontologia](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Grafo de Conceitos](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| 02 | [Representação de Conhecimento e Sistemas Especialistas](./lessons/2-Symbolic/README.md) | [Sistemas Especialistas](./lessons/2-Symbolic/Animals.ipynb) / [Ontologia](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Conceito de Grafo](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Introdução às Redes Neurais**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Laboratório](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Perceptron Multicamadas e Criando Nosso Próprio Framework](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Laboratório](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 04 | [Perceptron Multicamadas e Criando nosso próprio Framework](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Laboratório](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Introdução a Frameworks (PyTorch/TensorFlow) e Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Visão Computacional**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Explore Visão Computacional no Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Introdução à Visão Computacional. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Redes Neurais Convolucionais](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Arquiteturas de CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Redes Pré-treinadas e Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) e [Dicas de Treinamento](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoders e VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Redes Adversárias Generativas e Transferência de Estilo Artístico](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 10 | [Redes Adversárias Generativas & Transferência de Estilo Artístico](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Detecção de Objetos](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Segmentação Semântica. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Processamento de Linguagem Natural**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Explore Processamento de Linguagem Natural no Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Representação de Texto. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embeddings Semânticos de Palavras. Word2Vec e GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelagem de Linguagem. Treinando seus próprios embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Redes Neurais Recorrentes](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Redes Recorrentes Generativas](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Reconhecimento de Entidades Nomeadas](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Modelos de Linguagem Grandes, Programação de Prompts e Tarefas de Poucos Exemplos](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Representação de Texto. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embeddings Semânticos de Palavras. Word2Vec e GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelagem de Linguagem. Treinando seus próprios embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Redes Neurais Recorrentes](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Redes Recorrentes Generativas](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Reconhecimento de Entidades Nomeadas](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Modelos de Linguagem Grandes, Programação de Prompts e Tarefas de Few-Shot](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Outras Técnicas de IA** || |
| 21 | [Algoritmos Genéticos](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Aprendizado por Reforço Profundo](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -106,13 +106,13 @@ Para uma introdução mais leve aos tópicos de _IA na Nuvem_, você pode consid
## Cada lição contém
* Material de leitura prévia
* Notebooks Jupyter executáveis, que geralmente são específicos para o framework (**PyTorch** ou **TensorFlow**). O notebook executável também contém muito material teórico, então, para entender o tópico, é necessário passar por pelo menos uma versão do notebook (seja PyTorch ou TensorFlow).
* Jupyter Notebooks executáveis, que frequentemente são específicos para o framework (**PyTorch** ou **TensorFlow**). O notebook executável também contém muito material teórico, então para entender o tópico é necessário passar por pelo menos uma versão do notebook (PyTorch ou TensorFlow).
* **Labs** disponíveis para alguns tópicos, que oferecem a oportunidade de aplicar o material aprendido a um problema específico.
* Algumas seções contêm links para módulos do [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) que abordam tópicos relacionados.
## Começando
- Criamos uma [lição de configuração](./lessons/0-course-setup/setup.md) para ajudá-lo a configurar seu ambiente de desenvolvimento. - Para Educadores, criamos uma [lição de configuração de currículo](./lessons/0-course-setup/for-teachers.md) para você também!
- Criamos uma [lição de configuração](./lessons/0-course-setup/setup.md) para ajudar você a configurar seu ambiente de desenvolvimento. - Para Educadores, criamos também uma [lição de configuração de currículo](./lessons/0-course-setup/for-teachers.md)!
- Como [Executar o código no VSCode ou Codepace](./lessons/0-course-setup/how-to-run.md)
Siga estes passos:
@ -130,7 +130,7 @@ Junte-se ao nosso [servidor oficial de Discord de IA](https://aka.ms/genai-disco
Se você tiver feedback sobre o produto ou dúvidas enquanto desenvolve, visite nosso [Fórum de Desenvolvedores do Azure AI Foundry](https://aka.ms/foundry/forum)
## Questionários
> **Uma observação sobre os questionários**: Todos os questionários estão contidos na pasta Quiz-app em etc\quiz-app, ou [Online Aqui](https://ff-quizzes.netlify.app/). Eles estão vinculados às lições, o aplicativo de questionários pode ser executado localmente ou implantado no Azure; siga as instruções na pasta `quiz-app`. Eles estão sendo localizados gradualmente.
> **Uma observação sobre os questionários**: Todos os questionários estão contidos na pasta Quiz-app em etc\quiz-app, ou [Online Aqui](https://ff-quizzes.netlify.app/). Eles estão vinculados às lições, e o aplicativo de questionários pode ser executado localmente ou implantado no Azure; siga as instruções na pasta `quiz-app`. Eles estão sendo localizados gradualmente.
## Ajuda Necessária
Você tem sugestões ou encontrou erros de ortografia ou código? Abra uma issue ou crie um pull request.
@ -140,29 +140,29 @@ Você tem sugestões ou encontrou erros de ortografia ou código? Abra uma issue
* **✍️ Autor Principal:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Editora:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustradora de Sketchnotes:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Criadora do Quiz:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **✅ Criadora de Quiz:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Contribuidores Principais:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Outros Currículos
Nossa equipe produz outros currículos! Confira:
- [IA Generativa para Iniciantes](https://aka.ms/genai-beginners)
- [IA Generativa para Iniciantes .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [IA Generativa com JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [IA Generativa com Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [IA para Iniciantes](https://aka.ms/ai-beginners)
- [Ciência de Dados para Iniciantes](https://aka.ms/datascience-beginners)
- [Aprendizado de Máquina para Iniciantes](https://aka.ms/ml-beginners)
- [Cibersegurança para Iniciantes](https://github.com/microsoft/Security-101)
- [Desenvolvimento Web para Iniciantes](https://aka.ms/webdev-beginners)
- [IoT para Iniciantes](https://aka.ms/iot-beginners)
- [Desenvolvimento XR para Iniciantes](https://github.com/microsoft/xr-development-for-beginners)
- [Dominando o GitHub Copilot para Uso Agente](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Dominando o GitHub Copilot para Desenvolvedores C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Escolha Sua Própria Aventura com o Copilot](https://github.com/microsoft/CopilotAdventures)
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---
**Aviso Legal**:
Este documento foi traduzido utilizando o serviço de tradução por IA [Co-op Translator](https://github.com/Azure/co-op-translator). Embora nos esforcemos para garantir a precisão, esteja ciente de que traduções automáticas podem conter erros ou imprecisões. O documento original em seu idioma nativo deve ser considerado a fonte oficial. Para informações críticas, recomenda-se a tradução profissional realizada por humanos. Não nos responsabilizamos por quaisquer mal-entendidos ou interpretações equivocadas decorrentes do uso desta tradução.
Este documento foi traduzido utilizando o serviço de tradução por IA [Co-op Translator](https://github.com/Azure/co-op-translator). Embora nos esforcemos para garantir a precisão, esteja ciente de que traduções automatizadas podem conter erros ou imprecisões. O documento original em seu idioma nativo deve ser considerado a fonte autoritativa. Para informações críticas, recomenda-se a tradução profissional realizada por humanos. Não nos responsabilizamos por quaisquer mal-entendidos ou interpretações equivocadas decorrentes do uso desta tradução.

90
translations/cs/README.md
View File

@ -1,8 +1,8 @@
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@ -33,7 +33,7 @@ Prozkoumejte svět **umělé inteligence** (AI) s naším 12týdenním kurikulem
#### Podporováno prostřednictvím GitHub Action (automatizované a vždy aktuální)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](./README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
[Francouzština](../fr/README.md) | [Španělština](../es/README.md) | [Němčina](../de/README.md) | [Ruština](../ru/README.md) | [Arabština](../ar/README.md) | [Perština (Fársí)](../fa/README.md) | [Urdu](../ur/README.md) | [Čínština (zjednodušená)](../zh/README.md) | [Čínština (tradiční, Macao)](../mo/README.md) | [Čínština (tradiční, Hongkong)](../hk/README.md) | [Čínština (tradiční, Tchaj-wan)](../tw/README.md) | [Japonština](../ja/README.md) | [Korejština](../ko/README.md) | [Hindština](../hi/README.md) | [Bengálština](../bn/README.md) | [Maráthština](../mr/README.md) | [Nepálština](../ne/README.md) | [Panjábština (Gurmukhi)](../pa/README.md) | [Portugalština (Portugalsko)](../pt/README.md) | [Portugalština (Brazílie)](../br/README.md) | [Italština](../it/README.md) | [Polština](../pl/README.md) | [Turečtina](../tr/README.md) | [Řečtina](../el/README.md) | [Thajština](../th/README.md) | [Švédština](../sv/README.md) | [Dánština](../da/README.md) | [Norština](../no/README.md) | [Finština](../fi/README.md) | [Nizozemština](../nl/README.md) | [Hebrejština](../he/README.md) | [Vietnamština](../vi/README.md) | [Indonéština](../id/README.md) | [Malajština](../ms/README.md) | [Tagalog (Filipínština)](../tl/README.md) | [Svahilština](../sw/README.md) | [Maďarština](../hu/README.md) | [Čeština](./README.md) | [Slovenština](../sk/README.md) | [Rumunština](../ro/README.md) | [Bulharština](../bg/README.md) | [Srbština (cyrilice)](../sr/README.md) | [Chorvatština](../hr/README.md) | [Slovinština](../sl/README.md) | [Ukrajinština](../uk/README.md) | [Barmština (Myanmar)](../my/README.md)
**Pokud si přejete přidat další překlady, seznam podporovaných jazyků najdete [zde](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
@ -47,8 +47,8 @@ Prozkoumejte svět **umělé inteligence** (AI) s naším 12týdenním kurikulem
V tomto kurikulu se naučíte:
* Různé přístupy k umělé inteligenci, včetně "starého dobrého" symbolického přístupu s **reprezentací znalostí** a odvozováním ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neuronové sítě** a **hluboké učení**, které jsou jádrem moderní AI. Tyto důležité koncepty si vysvětlíme pomocí kódu ve dvou z nejpopulárnějších frameworků - [TensorFlow](http://Tensorflow.org) a [PyTorch](http://pytorch.org).
* **Neuronové architektury** pro práci s obrázky a textem. Pokryjeme nedávné modely, ale možná nebudeme zahrnovat nejnovější stav techniky.
* **Neuronové sítě** a **hluboké učení**, které jsou jádrem moderní AI. Koncepty těchto důležitých témat si ukážeme pomocí kódu ve dvou z nejpopulárnějších frameworků - [TensorFlow](http://Tensorflow.org) a [PyTorch](http://pytorch.org).
* **Neuronové architektury** pro práci s obrázky a textem. Pokryjeme nedávné modely, ale možná nebudeme zcela aktuální ve stavu nejnovějších technologií.
* Méně populární přístupy k AI, jako jsou **genetické algoritmy** a **systémy s více agenty**.
Co v tomto kurikulu nebudeme pokrývat:
@ -57,43 +57,43 @@ Co v tomto kurikulu nebudeme pokrývat:
* Obchodní případy využití **AI v podnikání**. Zvažte absolvování vzdělávací cesty [Úvod do AI pro obchodní uživatele](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) na Microsoft Learn nebo [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), vyvinuté ve spolupráci s [INSEAD](https://www.insead.edu/).
* **Klasické strojové učení**, které je dobře popsáno v našem [kurikulu Strojové učení pro začátečníky](http://github.com/Microsoft/ML-for-Beginners).
* Praktické aplikace AI postavené pomocí **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Pro toto doporučujeme začít s moduly Microsoft Learn pro [vidění](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [zpracování přirozeného jazyka](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generativní AI s Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** a další.
* Specifické ML **cloudové frameworky**, jako jsou [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) nebo [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Zvažte využití vzdělávacích cest [Vytváření a provozování řešení strojového učení s Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) a [Vytváření a provozování řešení strojového učení s Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Konverzační AI** a **chatovací boty**. Existuje samostatná vzdělávací cesta [Vytváření konverzačních AI řešení](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), a můžete se také podívat na [tento blogový příspěvek](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) pro více detailů.
* **Hluboká matematika** za hlubokým učením. Pro toto bychom doporučili knihu [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) od Iana Goodfellowa, Yoshuy Bengia a Aarona Courvillea, která je také dostupná online na [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Praktické aplikace AI vytvořené pomocí **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Pro začátek doporučujeme moduly Microsoft Learn pro [vidění](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [zpracování přirozeného jazyka](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generativní AI s Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** a další.
* Specifické ML **cloudové frameworky**, jako [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) nebo [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Zvažte využití vzdělávacích cest [Vytváření a provozování řešení strojového učení s Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) a [Vytváření a provozování řešení strojového učení s Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Konverzační AI** a **chatovací boty**. Existuje samostatná vzdělávací cesta [Vytváření konverzačních AI řešení](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) a můžete se také podívat na [tento blogový příspěvek](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) pro více detailů.
* **Hluboká matematika** za hlubokým učením. Pro toto doporučujeme knihu [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) od Iana Goodfellowa, Yoshuy Bengia a Aarona Courvillea, která je také dostupná online na [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Pro jemný úvod do témat _AI v cloudu_ můžete zvážit absolvování vzdělávací cesty [Začínáme s umělou inteligencí na Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Obsah
| | Odkaz na lekci | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Nastavení kurzu](./lessons/0-course-setup/setup.md) | [Nastavení vývojového prostředí](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Úvod do AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Úvod a historie AI](./lessons/1-Intro/README.md) | - | - |
| II | **Symbolická AI** |
| 02 | [Reprezentace znalostí a expertní systémy](./lessons/2-Symbolic/README.md) | [Expertní systémy](./lessons/2-Symbolic/Animals.ipynb) / [Ontologie](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Konceptuální graf](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Úvod do neuronových sítí**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Vícevrstvý perceptron a vytvoření vlastního frameworku](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Úvod do frameworků (PyTorch/TensorFlow) a overfittingu](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| | Odkaz na lekci | PyTorch/Keras/TensorFlow | Laboratorní cvičení |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Nastavení kurzu](./lessons/0-course-setup/setup.md) | [Nastavení vývojového prostředí](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Úvod do AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Úvod a historie AI](./lessons/1-Intro/README.md) | - | - |
| II | **Symbolická AI** |
| 02 | [Reprezentace znalostí a expertní systémy](./lessons/2-Symbolic/README.md) | [Expertní systémy](./lessons/2-Symbolic/Animals.ipynb) / [Ontologie](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Konceptuální graf](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Úvod do neuronových sítí**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Laboratorní cvičení](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Vícevrstvý perceptron a vytvoření vlastního frameworku](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Laboratorní cvičení](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Úvod do frameworků (PyTorch/TensorFlow) a přeučení](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Počítačové vidění**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Prozkoumejte počítačové vidění na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Úvod do počítačového vidění. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvoluční neuronové sítě](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Architektury CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Předtrénované sítě a transfer learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) a [Tréninkové triky](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 08 | [Předtrénované sítě a přenosové učení](./lessons/4-ComputerVision/08-TransferLearning/README.md) a [Tréninkové triky](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoenkodéry a VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generativní adversariální sítě a přenos uměleckého stylu](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 10 | [Generativní protivníkové sítě a přenos uměleckého stylu](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Detekce objektů](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantická segmentace. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Zpracování přirozeného jazyka**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Prozkoumejte zpracování přirozeného jazyka na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Reprezentace textu. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantické vektory slov. Word2Vec a GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Jazykové modelování. Trénink vlastních vektorů](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurentní neuronové sítě](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generativní rekurentní sítě](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformery. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Rozpoznávání pojmenovaných entit](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Velké jazykové modely, programování promptů a úlohy s malým počtem příkladů](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Reprezentace textu. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantické vektorové reprezentace slov. Word2Vec a GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelování jazyka. Trénink vlastních vektorových reprezentací](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurentní neuronové sítě](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generativní rekurentní sítě](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformery. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Rozpoznávání pojmenovaných entit](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Velké jazykové modely, programování promptů a úlohy s malým počtem příkladů](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Další techniky AI** || |
| 21 | [Genetické algoritmy](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Hluboké posilované učení](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -106,34 +106,34 @@ Pro jemný úvod do témat _AI v cloudu_ můžete zvážit absolvování vzděl
## Každá lekce obsahuje
* Materiály k předběžnému čtení
* Spustitelné Jupyter Notebooky, které jsou často specifické pro daný framework (**PyTorch** nebo **TensorFlow**). Notebook obsahuje také mnoho teoretického materiálu, takže pro pochopení tématu je nutné projít alespoň jednu verzi notebooku (buď PyTorch, nebo TensorFlow).
* **Lab** dostupné pro některá témata, které vám umožní vyzkoušet si aplikaci naučeného materiálu na konkrétní problém.
* Spustitelné Jupyter Notebooky, které jsou často specifické pro daný framework (**PyTorch** nebo **TensorFlow**). Spustitelný notebook obsahuje také mnoho teoretického materiálu, takže pro pochopení tématu je nutné projít alespoň jednu verzi notebooku (buď PyTorch nebo TensorFlow).
* **Lab** dostupné pro některá témata, které vám dávají příležitost vyzkoušet si aplikaci naučeného materiálu na konkrétní problém.
* Některé sekce obsahují odkazy na moduly [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum), které pokrývají související témata.
## Začínáme
- Připravili jsme [lekci o nastavení](./lessons/0-course-setup/setup.md), která vám pomůže s nastavením vývojového prostředí. - Pro pedagogy jsme vytvořili také [lekci o nastavení osnov](./lessons/0-course-setup/for-teachers.md)!
- Jak [spustit kód ve VSCode nebo CodeSpace](./lessons/0-course-setup/how-to-run.md)
- Vytvořili jsme [lekci pro nastavení](./lessons/0-course-setup/setup.md), která vám pomůže s nastavením vývojového prostředí. - Pro pedagogy jsme vytvořili také [lekci pro nastavení kurikula](./lessons/0-course-setup/for-teachers.md)!
- Jak [spustit kód ve VSCode nebo Codepace](./lessons/0-course-setup/how-to-run.md)
Postupujte podle těchto kroků:
Forkněte repozitář: Klikněte na tlačítko „Fork“ v pravém horním rohu této stránky.
Forkujte repozitář: Klikněte na tlačítko "Fork" v pravém horním rohu této stránky.
Naklonujte repozitář: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Klonujte repozitář: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Nezapomeňte si tento repozitář označit hvězdičkou (🌟), abyste ho později snadno našli.
Nezapomeňte označit hvězdičkou (🌟) tento repozitář, abyste ho později snadno našli.
## Seznamte se s ostatními studenty
Připojte se k našemu [oficiálnímu AI Discord serveru](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), kde se můžete setkat a propojit s dalšími studenty, kteří tento kurz absolvují, a získat podporu.
Připojte se k našemu [oficiálnímu AI Discord serveru](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), kde se můžete setkat a navázat kontakty s ostatními studenty, kteří absolvují tento kurz, a získat podporu.
Pokud máte zpětnou vazbu k produktu nebo otázky během práce, navštivte náš [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
Pokud máte zpětnou vazbu k produktu nebo otázky při budování, navštivte náš [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Kvízy
> **Poznámka k kvízům**: Všechny kvízy se nacházejí ve složce Quiz-app v etc\quiz-app, nebo [Online zde](https://ff-quizzes.netlify.app/). Jsou propojeny přímo z lekcí. Aplikaci pro kvízy lze spustit lokálně nebo nasadit na Azure; postupujte podle pokynů ve složce `quiz-app`. Postupně jsou lokalizovány.
> **Poznámka k kvízům**: Všechny kvízy jsou obsaženy ve složce Quiz-app v etc\quiz-app, nebo [Online zde](https://ff-quizzes.netlify.app/). Jsou propojeny přímo z lekcí, aplikaci kvízů lze spustit lokálně nebo nasadit na Azure; postupujte podle pokynů ve složce `quiz-app`. Postupně jsou lokalizovány.
## Hledáme pomoc
Máte nějaké návrhy nebo jste našli pravopisné či programové chyby? Vytvořte issue nebo pull request.
Máte návrhy nebo jste našli pravopisné či programové chyby? Vytvořte issue nebo pull request.
## Speciální poděkování
@ -143,9 +143,9 @@ Máte nějaké návrhy nebo jste našli pravopisné či programové chyby? Vytvo
* **✅ Tvůrce kvízů:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Hlavní přispěvatelé:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Další kurikula
## Další kurzy
Náš tým vytváří i další kurikula! Podívejte se na:
Náš tým vytváří i další kurzy! Podívejte se na:
- [Generativní AI pro začátečníky](https://aka.ms/genai-beginners)
- [Generativní AI pro začátečníky .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
@ -164,5 +164,5 @@ Náš tým vytváří i další kurikula! Podívejte se na:
---
**Upozornění**:
Tento dokument byl přeložen pomocí služby pro automatický překlad [Co-op Translator](https://github.com/Azure/co-op-translator). I když se snažíme o co největší přesnost, mějte prosím na paměti, že automatické překlady mohou obsahovat chyby nebo nepřesnosti. Původní dokument v jeho původním jazyce by měl být považován za závazný zdroj. Pro důležité informace doporučujeme profesionální lidský překlad. Neodpovídáme za žádná nedorozumění nebo nesprávné výklady vyplývající z použití tohoto překladu.
**Prohlášení**:
Tento dokument byl přeložen pomocí služby pro automatický překlad [Co-op Translator](https://github.com/Azure/co-op-translator). I když se snažíme o co největší přesnost, mějte prosím na paměti, že automatické překlady mohou obsahovat chyby nebo nepřesnosti. Za autoritativní zdroj by měl být považován původní dokument v jeho původním jazyce. Pro důležité informace doporučujeme profesionální lidský překlad. Neodpovídáme za žádná nedorozumění nebo nesprávné výklady vyplývající z použití tohoto překladu.

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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Kunstig intelligens for begyndere - Et undervisningsforløb
# Kunstig Intelligens for Begyndere - Et Læseplan
|![Sketchnote af @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.da.png)|
|:---:|
| AI For Beginners - _Sketchnote af [@girlie_mac](https://twitter.com/girlie_mac)_ |
|![Sketchnote af @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.da.png)|
|:---:|
| AI for begyndere - _Sketchnote af [@girlie_mac](https://twitter.com/girlie_mac)_ |
Udforsk verdenen af **Kunstig intelligens** (AI) med vores 12-ugers undervisningsforløb med 24 lektioner! Det inkluderer praktiske lektioner, quizzer og laboratorieøvelser. Forløbet er begyndervenligt og dækker værktøjer som TensorFlow og PyTorch samt etik inden for AI.
Udforsk verden af **Kunstig Intelligens** (AI) med vores 12-ugers, 24-lektioners læseplan! Den inkluderer praktiske lektioner, quizzer og laboratorier. Læseplanen er begyndervenlig og dækker værktøjer som TensorFlow og PyTorch samt etik inden for AI.
### 🌐 Understøttelse af flere sprog
### 🌐 Flersproget Support
#### Understøttet via GitHub Action (Automatisk & Altid opdateret)
#### Understøttet via GitHub Action (Automatiseret og altid opdateret)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](./README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
[Fransk](../fr/README.md) | [Spansk](../es/README.md) | [Tysk](../de/README.md) | [Russisk](../ru/README.md) | [Arabisk](../ar/README.md) | [Persisk (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Kinesisk (Forenklet)](../zh/README.md) | [Kinesisk (Traditionelt, Macau)](../mo/README.md) | [Kinesisk (Traditionelt, Hong Kong)](../hk/README.md) | [Kinesisk (Traditionelt, Taiwan)](../tw/README.md) | [Japansk](../ja/README.md) | [Koreansk](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepalesisk](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portugisisk (Portugal)](../pt/README.md) | [Portugisisk (Brasilien)](../br/README.md) | [Italiensk](../it/README.md) | [Polsk](../pl/README.md) | [Tyrkisk](../tr/README.md) | [Græsk](../el/README.md) | [Thai](../th/README.md) | [Svensk](../sv/README.md) | [Dansk](./README.md) | [Norsk](../no/README.md) | [Finsk](../fi/README.md) | [Hollandsk](../nl/README.md) | [Hebraisk](../he/README.md) | [Vietnamesisk](../vi/README.md) | [Indonesisk](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Ungarsk](../hu/README.md) | [Tjekkisk](../cs/README.md) | [Slovakisk](../sk/README.md) | [Rumænsk](../ro/README.md) | [Bulgarsk](../bg/README.md) | [Serbisk (Kyrillisk)](../sr/README.md) | [Kroatisk](../hr/README.md) | [Slovensk](../sl/README.md) | [Ukrainsk](../uk/README.md) | [Burmesisk (Myanmar)](../my/README.md)
**Hvis du ønsker yderligere oversættelser, kan understøttede sprog findes [her](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Hvis du ønsker yderligere oversættelser, kan understøttede sprog findes [her](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Bliv en del af fællesskabet
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Deltag i Fællesskabet
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Hvad du vil lære
## Hvad du vil lære
**[Mindmap over kurset](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[Mindmap over kurset](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
I dette undervisningsforløb vil du lære:
I denne læseplan vil du lære:
* Forskellige tilgange til Kunstig intelligens, herunder den "gode gamle" symbolske tilgang med **Vidensrepræsentation** og ræsonnement ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neurale netværk** og **Deep Learning**, som er kernen i moderne AI. Vi vil illustrere begreberne bag disse vigtige emner med kode i to af de mest populære frameworks - [TensorFlow](http://Tensorflow.org) og [PyTorch](http://pytorch.org).
* **Neurale arkitekturer** til arbejde med billeder og tekst. Vi vil dække nyere modeller, men muligvis ikke de allernyeste.
* Mindre populære AI-tilgange, såsom **Genetiske algoritmer** og **Multi-agent systemer**.
* Forskellige tilgange til Kunstig Intelligens, herunder den "gode gamle" symbolske tilgang med **Videnrepræsentation** og ræsonnement ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neurale Netværk** og **Deep Learning**, som er kernen i moderne AI. Vi vil illustrere koncepterne bag disse vigtige emner med kode i to af de mest populære frameworks - [TensorFlow](http://Tensorflow.org) og [PyTorch](http://pytorch.org).
* **Neurale Arkitekturer** til arbejde med billeder og tekst. Vi vil dække nyere modeller, men muligvis mangle lidt på det nyeste.
* Mindre populære AI-tilgange, såsom **Genetiske Algoritmer** og **Multi-Agent Systemer**.
Hvad vi ikke vil dække i dette undervisningsforløb:
Hvad vi ikke vil dække i denne læseplan:
> [Find alle yderligere ressourcer til dette kursus i vores Microsoft Learn-samling](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Find alle yderligere ressourcer til dette kursus i vores Microsoft Learn-samling](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Forretningsmæssige anvendelser af **AI i erhvervslivet**. Overvej at tage [Introduktion til AI for erhvervsbrugere](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) læringsforløb på Microsoft Learn, eller [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), udviklet i samarbejde med [INSEAD](https://www.insead.edu/).
* **Klassisk maskinlæring**, som er godt beskrevet i vores [Maskinlæring for begyndere undervisningsforløb](http://github.com/Microsoft/ML-for-Beginners).
* Praktiske AI-applikationer bygget med **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Til dette anbefaler vi, at du starter med modulerne Microsoft Learn for [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI med Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** og andre.
* Specifikke ML **Cloud Frameworks**, såsom [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), eller [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Overvej at bruge [Byg og drift maskinlæringsløsninger med Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) og [Byg og drift maskinlæringsløsninger med Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) læringsforløb.
* **Konversations-AI** og **Chatbots**. Der er et separat [Skab konversations-AI-løsninger](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) læringsforløb, og du kan også referere til [denne blogpost](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) for mere detaljeret information.
* **Avanceret matematik** bag deep learning. Til dette vil vi anbefale [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) af Ian Goodfellow, Yoshua Bengio og Aaron Courville, som også er tilgængelig online på [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Forretningscases for brug af **AI i erhvervslivet**. Overvej at tage [Introduktion til AI for forretningsbrugere](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) læringsstien på Microsoft Learn eller [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), udviklet i samarbejde med [INSEAD](https://www.insead.edu/).
* **Klassisk Maskinlæring**, som er godt beskrevet i vores [Maskinlæring for Begyndere Læseplan](http://github.com/Microsoft/ML-for-Beginners).
* Praktiske AI-applikationer bygget ved hjælp af **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Til dette anbefaler vi, at du starter med modulerne på Microsoft Learn for [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [naturlig sprogbehandling](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generativ AI med Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** og andre.
* Specifikke ML **Cloud Frameworks**, såsom [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) eller [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Overvej at bruge [Byg og drift maskinlæringsløsninger med Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) og [Byg og drift maskinlæringsløsninger med Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) læringsstier.
* **Samtale-AI** og **Chatbots**. Der er en separat [Opret samtale-AI-løsninger](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) læringssti, og du kan også henvise til [denne blogpost](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) for mere detaljer.
* **Avanceret Matematik** bag deep learning. Til dette vil vi anbefale [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) af Ian Goodfellow, Yoshua Bengio og Aaron Courville, som også er tilgængelig online på [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
For en blid introduktion til _AI i skyen_ emner kan du overveje at tage [Kom i gang med kunstig intelligens på Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) læringsforløb.
For en blid introduktion til _AI i skyen_ emner kan du overveje at tage [Kom i gang med kunstig intelligens på Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) læringsstien.
# Indhold
# Indhold
| | Lektion Link | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Opsætning af kursus](./lessons/0-course-setup/setup.md) | [Opsæt dit udviklingsmiljø](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Introduktion til AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Introduktion og AI's historie](./lessons/1-Intro/README.md) | - | - |
| II | **Symbolsk AI** |
| 02 | [Vidensrepræsentation og ekspertsystemer](./lessons/2-Symbolic/README.md) | [Ekspertsystemer](./lessons/2-Symbolic/Animals.ipynb) / [Ontologi](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Konceptgraf](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Introduktion til neurale netværk**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Multi-lag perceptron og opbygning af vores eget framework](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| | Lektion Link | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Opsætning af kursus](./lessons/0-course-setup/setup.md) | [Opsæt dit udviklingsmiljø](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Introduktion til AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Introduktion og AI's historie](./lessons/1-Intro/README.md) | - | - |
| II | **Symbolsk AI** |
| 02 | [Videnrepræsentation og Ekspertsystemer](./lessons/2-Symbolic/README.md) | [Ekspertsystemer](./lessons/2-Symbolic/Animals.ipynb) / [Ontologi](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Konceptgraf](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Introduktion til Neurale Netværk**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Multi-Layered Perceptron og Oprettelse af vores eget Framework](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Introduktion til Frameworks (PyTorch/TensorFlow) og Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Computer Vision**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Udforsk Computer Vision på Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Introduktion til Computer Vision. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
@ -86,14 +86,14 @@ For en blid introduktion til _AI i skyen_ emner kan du overveje at tage [Kom i g
| 11 | [Objektdetektion](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantisk Segmentering. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Udforsk Natural Language Processing på Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Tekstrepræsentation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantiske ordindlejringer. Word2Vec og GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Sprogmodellering. Træn dine egne indlejringer](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Navngiven Enhedsgenkendelse](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Store Sproglige Modeller, Prompt Programmering og Few-Shot Opgaver](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Tekstrepræsentation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantiske ordindlejringer. Word2Vec og GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Sprogmodellering. Træn dine egne indlejringer](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Navngiven Enhedsgenkendelse](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Store Sproglige Modeller, Prompt Programmering og Few-Shot Opgaver](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Andre AI-teknikker** || |
| 21 | [Genetiske Algoritmer](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Deep Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -121,7 +121,7 @@ Fork repositoryet: Klik på "Fork"-knappen øverst til højre på denne side.
Clone repositoryet: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Glem ikke at give stjerne (🌟) til dette repo for at finde det lettere senere.
Glem ikke at give stjerne (🌟) til dette repo for nemmere at finde det senere.
## Mød andre lærende
@ -145,7 +145,7 @@ Har du forslag eller fundet stave- eller kodefejl? Opret en issue eller lav en p
## Andre læseplaner
Vores team producerer andre læseplaner! Tjek dem ud:
Vores team producerer andre læseplaner! Tjek:
- [Generativ AI for begyndere](https://aka.ms/genai-beginners)
- [Generativ AI for begyndere .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
@ -158,11 +158,11 @@ Vores team producerer andre læseplaner! Tjek dem ud:
- [Webudvikling for begyndere](https://aka.ms/webdev-beginners)
- [IoT for begyndere](https://aka.ms/iot-beginners)
- [XR-udvikling for begyndere](https://github.com/microsoft/xr-development-for-beginners)
- [Mestre GitHub Copilot til agentisk brug](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mestre GitHub Copilot for C#/.NET udviklere](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Vælg dit eget Copilot-eventyr](https://github.com/microsoft/CopilotAdventures)
---
**Ansvarsfraskrivelse**:
Dette dokument er blevet oversat ved hjælp af AI-oversættelsestjenesten [Co-op Translator](https://github.com/Azure/co-op-translator). Selvom vi bestræber os på at sikre nøjagtighed, skal du være opmærksom på, at automatiserede oversættelser kan indeholde fejl eller unøjagtigheder. Det originale dokument på dets oprindelige sprog bør betragtes som den autoritative kilde. For kritisk information anbefales professionel menneskelig oversættelse. Vi påtager os ikke ansvar for eventuelle misforståelser eller fejltolkninger, der måtte opstå som følge af brugen af denne oversættelse.
Dette dokument er blevet oversat ved hjælp af AI-oversættelsestjenesten [Co-op Translator](https://github.com/Azure/co-op-translator). Selvom vi bestræber os på nøjagtighed, skal du være opmærksom på, at automatiserede oversættelser kan indeholde fejl eller unøjagtigheder. Det originale dokument på dets oprindelige sprog bør betragtes som den autoritative kilde. For kritisk information anbefales professionel menneskelig oversættelse. Vi påtager os intet ansvar for misforståelser eller fejltolkninger, der måtte opstå som følge af brugen af denne oversættelse.

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@ -1,8 +1,8 @@
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@ -21,13 +21,13 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Künstliche Intelligenz für Anfänger – Ein Curriculum
# Künstliche Intelligenz für Anfänger - Ein Lehrplan
|![Sketchnote von @girlie_mac https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|![Sketchnote von @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.de.png)|
|:---:|
| KI für Anfänger – _Sketchnote von [@girlie_mac](https://twitter.com/girlie_mac)_ |
| KI für Anfänger - _Sketchnote von [@girlie_mac](https://twitter.com/girlie_mac)_ |
Entdecken Sie die Welt der **Künstlichen Intelligenz** (KI) mit unserem 12-wöchigen Curriculum, das aus 24 Lektionen besteht! Es enthält praktische Lektionen, Quizze und Labore. Das Curriculum ist anfängerfreundlich und behandelt Tools wie TensorFlow und PyTorch sowie ethische Aspekte der KI.
Entdecke die Welt der **Künstlichen Intelligenz** (KI) mit unserem 12-wöchigen Lehrplan, bestehend aus 24 Lektionen! Er enthält praktische Übungen, Quizze und Labore. Der Lehrplan ist anfängerfreundlich und behandelt Tools wie TensorFlow und PyTorch sowie ethische Aspekte der KI.
### 🌐 Mehrsprachige Unterstützung
@ -35,47 +35,47 @@ Entdecken Sie die Welt der **Künstlichen Intelligenz** (KI) mit unserem 12-wöc
[Französisch](../fr/README.md) | [Spanisch](../es/README.md) | [Deutsch](./README.md) | [Russisch](../ru/README.md) | [Arabisch](../ar/README.md) | [Persisch (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinesisch (Vereinfacht)](../zh/README.md) | [Chinesisch (Traditionell, Macau)](../mo/README.md) | [Chinesisch (Traditionell, Hongkong)](../hk/README.md) | [Chinesisch (Traditionell, Taiwan)](../tw/README.md) | [Japanisch](../ja/README.md) | [Koreanisch](../ko/README.md) | [Hindi](../hi/README.md) | [Bengalisch](../bn/README.md) | [Marathi](../mr/README.md) | [Nepalesisch](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portugiesisch (Portugal)](../pt/README.md) | [Portugiesisch (Brasilien)](../br/README.md) | [Italienisch](../it/README.md) | [Polnisch](../pl/README.md) | [Türkisch](../tr/README.md) | [Griechisch](../el/README.md) | [Thailändisch](../th/README.md) | [Schwedisch](../sv/README.md) | [Dänisch](../da/README.md) | [Norwegisch](../no/README.md) | [Finnisch](../fi/README.md) | [Niederländisch](../nl/README.md) | [Hebräisch](../he/README.md) | [Vietnamesisch](../vi/README.md) | [Indonesisch](../id/README.md) | [Malaiisch](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Ungarisch](../hu/README.md) | [Tschechisch](../cs/README.md) | [Slowakisch](../sk/README.md) | [Rumänisch](../ro/README.md) | [Bulgarisch](../bg/README.md) | [Serbisch (Kyrillisch)](../sr/README.md) | [Kroatisch](../hr/README.md) | [Slowenisch](../sl/README.md) | [Ukrainisch](../uk/README.md) | [Birmanisch (Myanmar)](../my/README.md)
**Falls Sie zusätzliche Übersetzungen wünschen, finden Sie die unterstützten Sprachen [hier](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Falls du zusätzliche Übersetzungen wünschst, findest du die unterstützten Sprachen [hier](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Treten Sie der Community bei
## Werde Teil der Community
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Was Sie lernen werden
## Was du lernen wirst
**[Mindmap des Kurses](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
In diesem Curriculum lernen Sie:
In diesem Lehrplan wirst du lernen:
* Verschiedene Ansätze der Künstlichen Intelligenz, einschließlich des "klassischen" symbolischen Ansatzes mit **Wissensrepräsentation** und Schlussfolgerung ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neuronale Netze** und **Deep Learning**, die das Herzstück moderner KI bilden. Wir veranschaulichen die Konzepte hinter diesen wichtigen Themen mit Code in zwei der beliebtesten Frameworks – [TensorFlow](http://Tensorflow.org) und [PyTorch](http://pytorch.org).
* **Neuronale Architekturen** für die Arbeit mit Bildern und Text. Wir behandeln aktuelle Modelle, könnten aber bei den neuesten Entwicklungen etwas hinterherhinken.
* **Neuronale Netzwerke** und **Deep Learning**, die das Herzstück moderner KI bilden. Wir werden die Konzepte hinter diesen wichtigen Themen anhand von Code in zwei der beliebtesten Frameworks - [TensorFlow](http://Tensorflow.org) und [PyTorch](http://pytorch.org) - veranschaulichen.
* **Neuronale Architekturen** für die Arbeit mit Bildern und Text. Wir werden aktuelle Modelle behandeln, könnten jedoch bei den neuesten Entwicklungen etwas hinterherhinken.
* Weniger populäre KI-Ansätze wie **Genetische Algorithmen** und **Multi-Agenten-Systeme**.
Was wir in diesem Curriculum nicht behandeln:
Was wir in diesem Lehrplan nicht behandeln:
> [Finden Sie alle zusätzlichen Ressourcen für diesen Kurs in unserer Microsoft Learn-Sammlung](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Finde alle zusätzlichen Ressourcen für diesen Kurs in unserer Microsoft Learn Sammlung](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Geschäftsanwendungen von **KI im Business**. Ziehen Sie den Lernpfad [Einführung in KI für Geschäftsanwender](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) auf Microsoft Learn oder die [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) in Betracht, die in Zusammenarbeit mit [INSEAD](https://www.insead.edu/) entwickelt wurde.
* **Klassisches Machine Learning**, das in unserem [Machine Learning für Anfänger Curriculum](http://github.com/Microsoft/ML-for-Beginners) gut beschrieben ist.
* Praktische KI-Anwendungen, die mit **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** erstellt wurden. Dafür empfehlen wir, mit den Modulen auf Microsoft Learn für [Vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [Natural Language Processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI mit Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** und anderen zu beginnen.
* Spezifische ML-**Cloud-Frameworks** wie [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) oder [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Ziehen Sie die Lernpfade [Erstellen und Betreiben von Machine-Learning-Lösungen mit Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) und [Erstellen und Betreiben von Machine-Learning-Lösungen mit Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) in Betracht.
* **Konversationelle KI** und **Chatbots**. Es gibt einen separaten Lernpfad [Erstellen von konversationellen KI-Lösungen](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), und Sie können auch [diesen Blogbeitrag](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) für weitere Details heranziehen.
* **Tiefgehende Mathematik** hinter Deep Learning. Dafür empfehlen wir [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) von Ian Goodfellow, Yoshua Bengio und Aaron Courville, das auch online unter [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) verfügbar ist.
* Geschäftsanwendungen von **KI im Business**. Ziehe den Lernpfad [Einführung in KI für Geschäftsanwender](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) auf Microsoft Learn oder die [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), die in Zusammenarbeit mit [INSEAD](https://www.insead.edu/) entwickelt wurde, in Betracht.
* **Klassisches Machine Learning**, das in unserem [Machine Learning für Anfänger Lehrplan](http://github.com/Microsoft/ML-for-Beginners) gut beschrieben ist.
* Praktische KI-Anwendungen, die mit **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** erstellt wurden. Dafür empfehlen wir, mit den Modulen Microsoft Learn für [Vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [Natural Language Processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative KI mit Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** und anderen zu beginnen.
* Spezifische ML **Cloud-Frameworks**, wie [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) oder [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Ziehe die Lernpfade [Erstellen und Betreiben von Machine Learning-Lösungen mit Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) und [Erstellen und Betreiben von Machine Learning-Lösungen mit Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) in Betracht.
* **Konversationelle KI** und **Chatbots**. Es gibt einen separaten Lernpfad [Erstellen von konversationellen KI-Lösungen](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), und du kannst auch [diesen Blogbeitrag](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) für weitere Details heranziehen.
* **Tiefe Mathematik** hinter Deep Learning. Dafür empfehlen wir [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) von Ian Goodfellow, Yoshua Bengio und Aaron Courville, das auch online verfügbar ist unter [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Für eine sanfte Einführung in _KI in der Cloud_ können Sie den Lernpfad [Einführung in künstliche Intelligenz auf Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) in Betracht ziehen.
Für eine sanfte Einführung in _KI in der Cloud_ kannst du den Lernpfad [Einführung in künstliche Intelligenz auf Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) in Betracht ziehen.
# Inhalt
| | Lektion Link | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Kurs-Setup](./lessons/0-course-setup/setup.md) | [Einrichtung Ihrer Entwicklungsumgebung](./lessons/0-course-setup/how-to-run.md) | |
| 0 | [Kurs Setup](./lessons/0-course-setup/setup.md) | [Einrichtung deiner Entwicklungsumgebung](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Einführung in KI**](./lessons/1-Intro/README.md) | | |
| 01 | [Einführung und Geschichte der KI](./lessons/1-Intro/README.md) | - | - |
| II | **Symbolische KI** |
| 02 | [Wissensrepräsentation und Expertensysteme](./lessons/2-Symbolic/README.md) | [Expertensysteme](./lessons/2-Symbolic/Animals.ipynb) / [Ontologie](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Konzeptgraph](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Einführung in Neuronale Netze**](./lessons/3-NeuralNetworks/README.md) |||
| III | [**Einführung in neuronale Netzwerke**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perzeptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Mehrschichtige Perzeptrons und Erstellung eines eigenen Frameworks](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 04 | [Mehrschichtiges Perzeptron und Erstellung eines eigenen Frameworks](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Einführung in Frameworks (PyTorch/TensorFlow) und Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Computer Vision**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Erkunde Computer Vision auf Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Einführung in Computer Vision. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
@ -86,14 +86,14 @@ Für eine sanfte Einführung in _KI in der Cloud_ können Sie den Lernpfad [Einf
| 11 | [Objekterkennung](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantische Segmentierung. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Erkunde Natural Language Processing auf Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Textrepräsentation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantische Wort-Embeddings. Word2Vec und GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Sprachmodellierung. Eigene Embeddings trainieren](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Große Sprachmodelle, Prompt-Programmierung und Few-Shot-Aufgaben](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Textrepräsentation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantische Wort-Embeddings. Word2Vec und GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Sprachmodellierung. Eigene Embeddings trainieren](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Große Sprachmodelle, Prompt-Programmierung und Few-Shot-Aufgaben](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Andere KI-Techniken** || |
| 21 | [Genetische Algorithmen](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Deep Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -107,19 +107,19 @@ Für eine sanfte Einführung in _KI in der Cloud_ können Sie den Lernpfad [Einf
* Vorbereitendes Lesematerial
* Ausführbare Jupyter-Notebooks, die oft spezifisch für das Framework (**PyTorch** oder **TensorFlow**) sind. Das ausführbare Notebook enthält auch viele theoretische Inhalte, daher ist es wichtig, mindestens eine Version des Notebooks (entweder PyTorch oder TensorFlow) durchzugehen, um das Thema zu verstehen.
* **Labs**, die für einige Themen verfügbar sind und die Möglichkeit bieten, das Gelernte auf ein spezifisches Problem anzuwenden.
* **Labs**, die für einige Themen verfügbar sind und Ihnen die Möglichkeit geben, das Gelernte auf ein spezifisches Problem anzuwenden.
* Einige Abschnitte enthalten Links zu [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)-Modulen, die verwandte Themen abdecken.
## Erste Schritte
- Wir haben eine [Setup-Lektion](./lessons/0-course-setup/setup.md) erstellt, um Ihnen bei der Einrichtung Ihrer Entwicklungsumgebung zu helfen. - Für Lehrkräfte haben wir auch eine [Curricula-Setup-Lektion](./lessons/0-course-setup/for-teachers.md) erstellt!
- Wir haben eine [Setup-Lektion](./lessons/0-course-setup/setup.md) erstellt, um Ihnen bei der Einrichtung Ihrer Entwicklungsumgebung zu helfen. - Für Lehrkräfte haben wir ebenfalls eine [Curricula-Setup-Lektion](./lessons/0-course-setup/for-teachers.md) erstellt!
- Wie man [den Code in VSCode oder einem Codespace ausführt](./lessons/0-course-setup/how-to-run.md)
Folgen Sie diesen Schritten:
Repository forken: Klicken Sie auf die Schaltfläche "Fork" oben rechts auf dieser Seite.
Forken Sie das Repository: Klicken Sie auf die Schaltfläche "Fork" oben rechts auf dieser Seite.
Repository klonen: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Klonen Sie das Repository: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Vergessen Sie nicht, dieses Repository mit einem Stern (🌟) zu markieren, um es später leichter zu finden.
@ -127,7 +127,7 @@ Vergessen Sie nicht, dieses Repository mit einem Stern (🌟) zu markieren, um e
Treten Sie unserem [offiziellen AI Discord-Server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) bei, um andere Lernende kennenzulernen, sich zu vernetzen und Unterstützung zu erhalten.
Wenn Sie Produktfeedback oder Fragen beim Bauen haben, besuchen Sie unser [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
Wenn Sie Produktfeedback oder Fragen während des Aufbaus haben, besuchen Sie unser [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Quiz
> **Eine Anmerkung zu den Quiz**: Alle Quiz befinden sich im Ordner Quiz-app unter etc\quiz-app oder [Online Hier](https://ff-quizzes.netlify.app/). Sie sind aus den Lektionen heraus verlinkt. Die Quiz-App kann lokal ausgeführt oder auf Azure bereitgestellt werden; folgen Sie den Anweisungen im Ordner `quiz-app`. Sie werden nach und nach lokalisiert.
@ -165,4 +165,4 @@ Unser Team erstellt auch andere Lehrpläne! Schau dir diese an:
---
**Haftungsausschluss**:
Dieses Dokument wurde mit dem KI-Übersetzungsdienst [Co-op Translator](https://github.com/Azure/co-op-translator) übersetzt. Obwohl wir uns um Genauigkeit bemühen, beachten Sie bitte, dass automatisierte Übersetzungen Fehler oder Ungenauigkeiten enthalten können. Das Originaldokument in seiner ursprünglichen Sprache sollte als maßgebliche Quelle betrachtet werden. Für kritische Informationen wird eine professionelle menschliche Übersetzung empfohlen. Wir übernehmen keine Haftung für Missverständnisse oder Fehlinterpretationen, die sich aus der Nutzung dieser Übersetzung ergeben.
Dieses Dokument wurde mithilfe des KI-Übersetzungsdienstes [Co-op Translator](https://github.com/Azure/co-op-translator) übersetzt. Obwohl wir uns um Genauigkeit bemühen, weisen wir darauf hin, dass automatisierte Übersetzungen Fehler oder Ungenauigkeiten enthalten können. Das Originaldokument in seiner ursprünglichen Sprache sollte als maßgebliche Quelle betrachtet werden. Für kritische Informationen wird eine professionelle menschliche Übersetzung empfohlen. Wir übernehmen keine Haftung für Missverständnisse oder Fehlinterpretationen, die sich aus der Nutzung dieser Übersetzung ergeben.

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@ -1,8 +1,8 @@
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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Τεχνητή Νοημοσύνη για Αρχάριους - Ένα Πρόγραμμα Σπουδών
# Τεχνητή Νοημοσύνη για Αρχάριους - Ένα Εκπαιδευτικό Πρόγραμμα
|![Σκίτσο από την @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.el.png)|
|![Σκίτσο από @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.el.png)|
|:---:|
| Τεχνητή Νοημοσύνη για Αρχάριους - _Σκίτσο από την [@girlie_mac](https://twitter.com/girlie_mac)_ |
| Τεχνητή Νοημοσύνη για Αρχάριους - _Σκίτσο από [@girlie_mac](https://twitter.com/girlie_mac)_ |
Εξερευνήστε τον κόσμο της **Τεχνητής Νοημοσύνης** (AI) με το 12-εβδομάδων, 24-μαθημάτων πρόγραμμα σπουδών μας! Περιλαμβάνει πρακτικά μαθήματα, κουίζ και εργαστήρια. Το πρόγραμμα είναι φιλικό για αρχάριους και καλύπτει εργαλεία όπως το TensorFlow και το PyTorch, καθώς και θέματα ηθικής στην Τεχνητή Νοημοσύνη.
Εξερευνήστε τον κόσμο της **Τεχνητής Νοημοσύνης** (AI) με το εκπαιδευτικό μας πρόγραμμα διάρκειας 12 εβδομάδων και 24 μαθημάτων! Περιλαμβάνει πρακτικά μαθήματα, κουίζ και εργαστήρια. Το πρόγραμμα είναι φιλικό για αρχάριους και καλύπτει εργαλεία όπως το TensorFlow και το PyTorch, καθώς και θέματα ηθικής στην Τεχνητή Νοημοσύνη.
### 🌐 Υποστήριξη Πολλαπλών Γλωσσών
#### Υποστηρίζεται μέσω GitHub Action (Αυτόματα & Πάντα Ενημερωμένο)
#### Υποστηρίζεται μέσω GitHub Action (Αυτοματοποιημένο & Πάντα Ενημερωμένο)
[Γαλλικά](../fr/README.md) | [Ισπανικά](../es/README.md) | [Γερμανικά](../de/README.md) | [Ρωσικά](../ru/README.md) | [Αραβικά](../ar/README.md) | [Περσικά (Φαρσί)](../fa/README.md) | [Ουρντού](../ur/README.md) | [Κινέζικα (Απλοποιημένα)](../zh/README.md) | [Κινέζικα (Παραδοσιακά, Μακάο)](../mo/README.md) | [Κινέζικα (Παραδοσιακά, Χονγκ Κονγκ)](../hk/README.md) | [Κινέζικα (Παραδοσιακά, Ταϊβάν)](../tw/README.md) | [Ιαπωνικά](../ja/README.md) | [Κορεατικά](../ko/README.md) | [Χίντι](../hi/README.md) | [Μπενγκάλι](../bn/README.md) | [Μαραθικά](../mr/README.md) | [Νεπαλικά](../ne/README.md) | [Παντζάμπι (Γκουρμούκι)](../pa/README.md) | [Πορτογαλικά (Πορτογαλία)](../pt/README.md) | [Πορτογαλικά (Βραζιλία)](../br/README.md) | [Ιταλικά](../it/README.md) | [Πολωνικά](../pl/README.md) | [Τουρκικά](../tr/README.md) | [Ελληνικά](./README.md) | [Ταϊλανδικά](../th/README.md) | [Σουηδικά](../sv/README.md) | [Δανικά](../da/README.md) | [Νορβηγικά](../no/README.md) | [Φινλανδικά](../fi/README.md) | [Ολλανδικά](../nl/README.md) | [Εβραϊκά](../he/README.md) | [Βιετναμέζικα](../vi/README.md) | [Ινδονησιακά](../id/README.md) | [Μαλαϊκά](../ms/README.md) | [Ταγκαλόγκ (Φιλιππινέζικα)](../tl/README.md) | [Σουαχίλι](../sw/README.md) | [Ουγγρικά](../hu/README.md) | [Τσέχικα](../cs/README.md) | [Σλοβακικά](../sk/README.md) | [Ρουμανικά](../ro/README.md) | [Βουλγαρικά](../bg/README.md) | [Σερβικά (Κυριλλικά)](../sr/README.md) | [Κροατικά](../hr/README.md) | [Σλοβενικά](../sl/README.md) | [Ουκρανικά](../uk/README.md) | [Βιρμανικά (Μιανμάρ)](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](./README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Αν θέλετε να υποστηριχθούν επιπλέον γλώσσες, μπορείτε να δείτε τη λίστα [εδώ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Αν επιθυμείτε να υποστηριχθούν επιπλέον γλώσσες, οι διαθέσιμες γλώσσες παρατίθενται [εδώ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Γίνετε Μέλος της Κοινότητας
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -44,27 +44,27 @@ CO_OP_TRANSLATOR_METADATA:
**[Διάγραμμα Μαθήματος](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
Σε αυτό το πρόγραμμα σπουδών, θα μάθετε:
Σε αυτό το εκπαιδευτικό πρόγραμμα, θα μάθετε:
* Διάφορες προσεγγίσεις στην Τεχνητή Νοημοσύνη, συμπεριλαμβανομένης της "παραδοσιακής" συμβολικής προσέγγισης με **Αναπαράσταση Γνώσης** και συλλογισμό ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* Διάφορες προσεγγίσεις στην Τεχνητή Νοημοσύνη, συμπεριλαμβανομένης της "παραδοσιακής" συμβολικής προσέγγισης με **Αναπαράσταση Γνώσης** και λογική ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Νευρωνικά Δίκτυα** και **Βαθιά Μάθηση**, που αποτελούν τον πυρήνα της σύγχρονης Τεχνητής Νοημοσύνης. Θα εξηγήσουμε τις έννοιες πίσω από αυτά τα σημαντικά θέματα χρησιμοποιώντας κώδικα σε δύο από τα πιο δημοφιλή πλαίσια - [TensorFlow](http://Tensorflow.org) και [PyTorch](http://pytorch.org).
* **Νευρωνικές Αρχιτεκτονικές** για εργασία με εικόνες και κείμενο. Θα καλύψουμε πρόσφατα μοντέλα, αλλά ίσως να μην περιλαμβάνουμε τα πιο σύγχρονα.
* Λιγότερο δημοφιλείς προσεγγίσεις στην Τεχνητή Νοημοσύνη, όπως οι **Γενετικοί Αλγόριθμοι** και τα **Πολυπρακτορικά Συστήματα**.
* **Νευρωνικές Αρχιτεκτονικές** για εργασία με εικόνες και κείμενο. Θα καλύψουμε πρόσφατα μοντέλα, αν και μπορεί να μην περιλαμβάνουμε την αιχμή της τεχνολογίας.
* Λιγότερο δημοφιλείς προσεγγίσεις στην Τεχνητή Νοημοσύνη, όπως **Γενετικοί Αλγόριθμοι** και **Συστήματα Πολλαπλών Πρακτόρων**.
Τι δεν θα καλύψουμε σε αυτό το πρόγραμμα σπουδών:
Τι δεν θα καλύψουμε σε αυτό το εκπαιδευτικό πρόγραμμα:
> [Βρείτε όλους τους επιπλέον πόρους για αυτό το μάθημα στη συλλογή μας στο Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Βρείτε όλους τους πρόσθετους πόρους για αυτό το μάθημα στη συλλογή μας στο Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Επιχειρηματικές περιπτώσεις χρήσης της **Τεχνητής Νοημοσύνης στις Επιχειρήσεις**. Σκεφτείτε να παρακολουθήσετε το [Εισαγωγή στην Τεχνητή Νοημοσύνη για επιχειρηματικούς χρήστες](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) ή το [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), που αναπτύχθηκε σε συνεργασία με το [INSEAD](https://www.insead.edu/).
* **Κλασική Μηχανική Μάθηση**, η οποία περιγράφεται καλά στο [Πρόγραμμα Σπουδών Μηχανικής Μάθησης για Αρχάριους](http://github.com/Microsoft/ML-for-Beginners).
* Πρακτικές εφαρμογές Τεχνητής Νοημοσύνης που χρησιμοποιούν **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Για αυτό, προτείνουμε να ξεκινήσετε με τα μαθήματα του Microsoft Learn για [όραση](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [επεξεργασία φυσικής γλώσσας](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Γενετική Τεχνητή Νοημοσύνη με την Υπηρεσία Azure OpenAI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** και άλλα.
* Συγκεκριμένα **Cloud Frameworks** για Μηχανική Μάθηση, όπως το [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), το [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) ή το [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Σκεφτείτε να χρησιμοποιήσετε τα μαθήματα [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) και [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Συνομιλιακή Τεχνητή Νοημοσύνη** και **Chat Bots**. Υπάρχει ένα ξεχωριστό [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) μάθημα, και μπορείτε επίσης να ανατρέξετε σε [αυτήν την ανάρτηση στο blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) για περισσότερες λεπτομέρειες.
* **Βαθιά Μαθηματικά** πίσω από τη βαθιά μάθηση. Για αυτό, θα προτείναμε το [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) από τους Ian Goodfellow, Yoshua Bengio και Aaron Courville, το οποίο είναι επίσης διαθέσιμο online στο [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Επιχειρηματικές περιπτώσεις χρήσης της **Τεχνητής Νοημοσύνης στις Επιχειρήσεις**. Σκεφτείτε να παρακολουθήσετε το [Εισαγωγή στην Τεχνητή Νοημοσύνη για επιχειρηματικούς χρήστες](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) στο Microsoft Learn ή το [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), που αναπτύχθηκε σε συνεργασία με το [INSEAD](https://www.insead.edu/).
* **Κλασική Μηχανική Μάθηση**, που περιγράφεται καλά στο [Εκπαιδευτικό Πρόγραμμα Μηχανικής Μάθησης για Αρχάριους](http://github.com/Microsoft/ML-for-Beginners).
* Πρακτικές εφαρμογές Τεχνητής Νοημοσύνης που κατασκευάζονται χρησιμοποιώντας **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Για αυτό, προτείνουμε να ξεκινήσετε με τα modules του Microsoft Learn για [όραση](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [επεξεργασία φυσικής γλώσσας](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Γενετική Τεχνητή Νοημοσύνη με την Υπηρεσία Azure OpenAI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** και άλλα.
* Συγκεκριμένα **Cloud Frameworks** για Μηχανική Μάθηση, όπως [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) ή [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Σκεφτείτε να χρησιμοποιήσετε τα εκπαιδευτικά μονοπάτια [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) και [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Συνομιλιακή Τεχνητή Νοημοσύνη** και **Chat Bots**. Υπάρχει ξεχωριστό [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) εκπαιδευτικό μονοπάτι, και μπορείτε επίσης να ανατρέξετε σε [αυτήν την ανάρτηση στο blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) για περισσότερες λεπτομέρειες.
* **Βαθιά Μαθηματικά** πίσω από τη βαθιά μάθηση. Για αυτό, θα προτείναμε το [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) από τους Ian Goodfellow, Yoshua Bengio και Aaron Courville, που είναι επίσης διαθέσιμο online στο [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Για μια ήπια εισαγωγή στα θέματα _AI στο Cloud_, μπορείτε να παρακολουθήσετε το [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) μάθημα.
Για μια ήπια εισαγωγή στα θέματα _Τεχνητής Νοημοσύνης στο Cloud_, μπορείτε να σκεφτείτε να παρακολουθήσετε το [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) εκπαιδευτικό μονοπάτι.
# Περιεχόμενα
# Περιεχόμενο
| | Σύνδεσμος Μαθήματος | PyTorch/Keras/TensorFlow | Εργαστήριο |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
@ -72,43 +72,43 @@ CO_OP_TRANSLATOR_METADATA:
| I | [**Εισαγωγή στην Τεχνητή Νοημοσύνη**](./lessons/1-Intro/README.md) | | |
| 01 | [Εισαγωγή και Ιστορία της Τεχνητής Νοημοσύνης](./lessons/1-Intro/README.md) | - | - |
| II | **Συμβολική Τεχνητή Νοημοσύνη** |
| 02 | [Αναπαράσταση Γνώσης και Εξειδικευμένα Συστήματα](./lessons/2-Symbolic/README.md) | [Εξειδικευμένα Συστήματα](./lessons/2-Symbolic/Animals.ipynb) / [Οντολογία](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Γράφημα Εννοιών](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| 02 | [Αναπαράσταση Γνώσης και Συστήματα Ειδικών](./lessons/2-Symbolic/README.md) | [Συστήματα Ειδικών](./lessons/2-Symbolic/Animals.ipynb) / [Οντολογία](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Γράφος Εννοιών](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Εισαγωγή στα Νευρωνικά Δίκτυα**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Εργαστήριο](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Πολυεπίπεδο Perceptron και Δημιουργία του Δικού μας Πλαισίου](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Εργαστήριο](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 04 | [Πολυεπίπεδο Perceptron και Δημιουργία του δικού μας Πλαισίου](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Εργαστήριο](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Εισαγωγή στα Frameworks (PyTorch/TensorFlow) και Υπερπροσαρμογή](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Εργαστήριο](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Υπολογιστική Όραση**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Εξερεύνηση Υπολογιστικής Όρασης στο Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Εισαγωγή στην Υπολογιστική Όραση. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Εργαστήριο](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| IV | [**Όραση Υπολογιστών**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Εξερεύνηση Όρασης Υπολογιστών στο Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Εισαγωγή στην Όραση Υπολογιστών. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Σημειωματάριο](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Εργαστήριο](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Συνελικτικά Νευρωνικά Δίκτυα](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Αρχιτεκτονικές CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Εργαστήριο](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Προεκπαιδευμένα Δίκτυα και Μεταφορά Μάθησης](./lessons/4-ComputerVision/08-TransferLearning/README.md) και [Τεχνικές Εκπαίδευσης](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Εργαστήριο](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Αυτοκωδικοποιητές και VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Γενετικά Ανταγωνιστικά Δίκτυα & Μεταφορά Καλλιτεχνικού Στυλ](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 10 | [Δίκτυα Αντιπαραγωγής και Μεταφορά Καλλιτεχνικού Στυλ](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Ανίχνευση Αντικειμένων](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Εργαστήριο](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Σημασιολογική Τμηματοποίηση. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Επεξεργασία Φυσικής Γλώσσας**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Εξερεύνηση Επεξεργασίας Φυσικής Γλώσσας στο Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Αναπαράσταση Κειμένου. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Σημασιολογικές Ενσωματώσεις Λέξεων. Word2Vec και GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Μοντελοποίηση Γλώσσας. Εκπαίδευση δικών σας ενσωματώσεων](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Εργαστήριο](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Επαναληπτικά Νευρωνικά Δίκτυα](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Γενετικά Επαναληπτικά Δίκτυα](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Εργαστήριο](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Μετασχηματιστές. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Αναγνώριση Οντοτήτων](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Εργαστήριο](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Μεγάλα Μοντέλα Γλώσσας, Προγραμματισμός Προτροπών και Εργασίες Λίγων Παραδειγμάτων](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Αναπαράσταση Κειμένου. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Σημασιολογικές Ενσωματώσεις Λέξεων. Word2Vec και GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Μοντελοποίηση Γλώσσας. Εκπαίδευση δικών σας Ενσωματώσεων](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Εργαστήριο](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Επαναληπτικά Νευρωνικά Δίκτυα](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Γενετικά Επαναληπτικά Δίκτυα](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Εργαστήριο](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Μετασχηματιστές. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Αναγνώριση Οντοτήτων](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Εργαστήριο](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Μεγάλα Μοντέλα Γλώσσας, Προγραμματισμός Προτροπών και Εργασίες Λίγων Παραδειγμάτων](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Άλλες Τεχνικές AI** || |
| 21 | [Γενετικοί Αλγόριθμοι](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 21 | [Γενετικοί Αλγόριθμοι](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Σημειωματάριο](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Βαθιά Ενισχυτική Μάθηση](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Εργαστήριο](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Συστήματα Πολλαπλών Πρακτόρων](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Ηθική AI** | | |
| 24 | [Ηθική AI και Υπεύθυνη AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Αρχές Υπεύθυνης AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Επιπλέον** | | |
| 25 | [Δίκτυα Πολλαπλών Τρόπων, CLIP και VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 25 | [Δίκτυα Πολλαπλών Τρόπων, CLIP και VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Σημειωματάριο](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Κάθε μάθημα περιλαμβάνει
* Υλικό προετοιμασίας
* Εκτελέσιμα Jupyter Notebooks, τα οποία συχνά είναι ειδικά για το framework (**PyTorch** ή **TensorFlow**). Το εκτελέσιμο notebook περιέχει επίσης πολύ θεωρητικό υλικό, οπότε για να κατανοήσετε το θέμα πρέπει να διαβάσετε τουλάχιστον μία έκδοση του notebook (είτε PyTorch είτε TensorFlow).
* Εκτελέσιμα Jupyter Notebooks, που συχνά είναι ειδικά για το framework (**PyTorch** ή **TensorFlow**). Το εκτελέσιμο notebook περιέχει επίσης πολύ θεωρητικό υλικό, οπότε για να κατανοήσετε το θέμα πρέπει να μελετήσετε τουλάχιστον μία έκδοση του notebook (είτε PyTorch είτε TensorFlow).
* **Εργαστήρια** διαθέσιμα για ορισμένα θέματα, που σας δίνουν την ευκαιρία να εφαρμόσετε το υλικό που έχετε μάθει σε ένα συγκεκριμένο πρόβλημα.
* Ορισμένες ενότητες περιέχουν συνδέσμους σε [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) modules που καλύπτουν σχετικά θέματα.
* Ορισμένες ενότητες περιέχουν συνδέσμους σε [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) modules που καλύπτουν συναφή θέματα.
## Ξεκινώντας
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Ακολουθήστε αυτά τα βήματα:
Κλωνοποιήστε το Αποθετήριο: Πατήστε το κουμπί "Fork" στην επάνω δεξιά γωνία αυτής της σελίδας.
Κλωνοποίηση του Αποθετηρίου: Πατήστε το κουμπί "Fork" στην επάνω δεξιά γωνία αυτής της σελίδας.
Κλωνοποιήστε το Αποθετήριο: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Κλωνοποίηση του Αποθετηρίου: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Μην ξεχάσετε να βάλετε αστέρι (🌟) σε αυτό το αποθετήριο για να το βρίσκετε πιο εύκολα αργότερα.
Μην ξεχάσετε να βάλετε αστέρι (🌟) σε αυτό το repo για να το βρείτε πιο εύκολα αργότερα.
## Γνωρίστε άλλους Εκπαιδευόμενους
@ -130,7 +130,7 @@ CO_OP_TRANSLATOR_METADATA:
Αν έχετε σχόλια για το προϊόν ή ερωτήσεις κατά τη δημιουργία, επισκεφθείτε το [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Κουίζ
> **Σημείωση σχετικά με τα κουίζ**: Όλα τα κουίζ βρίσκονται στον φάκελο Quiz-app στο etc\quiz-app, ή [Online Εδώ](https://ff-quizzes.netlify.app/). Συνδέονται μέσα από τα μαθήματα. Η εφαρμογή κουίζ μπορεί να εκτελεστεί τοπικά ή να αναπτυχθεί στο Azure. Ακολουθήστε τις οδηγίες στον φάκελο `quiz-app`. Γίνονται σταδιακά τοπικοποιήσεις.
> **Σημείωση σχετικά με τα κουίζ**: Όλα τα κουίζ βρίσκονται στον φάκελο Quiz-app στο etc\quiz-app, ή [Online Εδώ](https://ff-quizzes.netlify.app/). Συνδέονται μέσα από τα μαθήματα και η εφαρμογή κουίζ μπορεί να εκτελεστεί τοπικά ή να αναπτυχθεί στο Azure. Ακολουθήστε τις οδηγίες στον φάκελο `quiz-app`. Γίνονται σταδιακά τοπικοποιήσεις.
## Ζητείται Βοήθεια
Έχετε προτάσεις ή βρήκατε ορθογραφικά ή λάθη στον κώδικα; Δημιουργήστε ένα ζήτημα ή υποβάλετε ένα pull request.
@ -138,28 +138,28 @@ CO_OP_TRANSLATOR_METADATA:
## Ειδικές Ευχαριστίες
* **✍️ Κύριος Συγγραφέας:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Επιμελήτρια:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🔥 Συντάκτρια:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Εικονογράφος Sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Δημιουργός Κουίζ:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Κύριοι Συνεισφέροντες:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **🙏 Βασικοί Συνεργάτες:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Άλλα Προγράμματα Σπουδών
Η ομάδα μας δημιουργεί και άλλα προγράμματα σπουδών! Ρίξτε μια ματιά:
Η ομάδα μας δημιουργεί και άλλα προγράμματα σπουδών! Δείτε:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Generative AI για Αρχάριους](https://aka.ms/genai-beginners)
- [Generative AI για Αρχάριους .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI με JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI με Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI για Αρχάριους](https://aka.ms/ai-beginners)
- [Επιστήμη Δεδομένων για Αρχάριους](https://aka.ms/datascience-beginners)
- [Μηχανική Μάθηση για Αρχάριους](https://aka.ms/ml-beginners)
- [Κυβερνοασφάλεια για Αρχάριους](https://github.com/microsoft/Security-101)
- [Web Development για Αρχάριους](https://aka.ms/webdev-beginners)
- [IoT για Αρχάριους](https://aka.ms/iot-beginners)
- [Ανάπτυξη XR για Αρχάριους](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot για Agentic χρήση](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot για Προγραμματιστές C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---

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@ -27,7 +27,7 @@ CO_OP_TRANSLATOR_METADATA:
|:---:|
| AI For Beginners - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ |
Dive into the fascinating world of **Artificial Intelligence** (AI) with our 12-week, 24-lesson curriculum! It features hands-on lessons, quizzes, and labs. This beginner-friendly curriculum introduces tools like TensorFlow and PyTorch, along with discussions on AI ethics.
Dive into the fascinating world of **Artificial Intelligence** (AI) with this 12-week, 24-lesson curriculum! It includes hands-on lessons, quizzes, and labs. Designed for beginners, it covers tools like TensorFlow and PyTorch, along with discussions on AI ethics.
### 🌐 Multi-Language Support
@ -47,15 +47,15 @@ Dive into the fascinating world of **Artificial Intelligence** (AI) with our 12-
This curriculum will teach you:
* Various approaches to Artificial Intelligence, including the classic symbolic approach with **Knowledge Representation** and reasoning ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neural Networks** and **Deep Learning**, the foundation of modern AI. You'll learn the concepts behind these topics through code examples in two popular frameworks - [TensorFlow](http://Tensorflow.org) and [PyTorch](http://pytorch.org).
* **Neural Networks** and **Deep Learning**, the foundation of modern AI. You'll learn the concepts behind these topics using code in two popular frameworks - [TensorFlow](http://Tensorflow.org) and [PyTorch](http://pytorch.org).
* **Neural Architectures** for processing images and text. While we’ll cover recent models, we may not delve into the latest advancements.
* Less common AI techniques, such as **Genetic Algorithms** and **Multi-Agent Systems**.
* Less common AI methods, such as **Genetic Algorithms** and **Multi-Agent Systems**.
What this curriculum does not cover:
> [Find all additional resources for this course in our Microsoft Learn collection](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Business applications of **AI in Business**. For this, consider the [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) learning path on Microsoft Learn or [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), developed in collaboration with [INSEAD](https://www.insead.edu/).
* Business applications of **AI in Business**. For this, consider the [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) learning path on Microsoft Learn, or [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), developed in collaboration with [INSEAD](https://www.insead.edu/).
* **Classic Machine Learning**, which is thoroughly covered in our [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners).
* Practical AI applications using **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. For this, start with Microsoft Learn modules for [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)**, and more.
* Specific ML **Cloud Frameworks**, such as [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), or [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Consider the learning paths [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) and [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
@ -86,14 +86,14 @@ For a beginner-friendly introduction to _AI in the Cloud_, consider the [Get sta
| 11 | [Object Detection](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantic Segmentation. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Explore Natural Language Processing on Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Text Representation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantic word embeddings. Word2Vec and GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Language Modeling. Training your own embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Large Language Models, Prompt Programming and Few-Shot Tasks](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Text Representation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantic word embeddings. Word2Vec and GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Language Modeling. Training your own embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Large Language Models, Prompt Programming and Few-Shot Tasks](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Other AI Techniques** || |
| 21 | [Genetic Algorithms](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Deep Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -130,7 +130,7 @@ Join our [official AI Discord server](https://aka.ms/genai-discord?WT.mc_id=acad
If you have product feedback or questions whilst building visit our [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Quizzes
> **A note about quizzes**: All quizzes are located in the Quiz-app folder under etc\quiz-app, or [Online Here](https://ff-quizzes.netlify.app/). They are linked within the lessons. The quiz app can be run locally or deployed to Azure; follow the instructions in the `quiz-app` folder. Localization is being done progressively.
> **A note about quizzes**: All quizzes are located in the Quiz-app folder in etc\quiz-app, or [Online Here](https://ff-quizzes.netlify.app/). They are linked within the lessons. The quiz app can be run locally or deployed to Azure; follow the instructions in the `quiz-app` folder. Localization is being done gradually.
## Help Wanted
Do you have suggestions or have you found spelling or code errors? Feel free to open an issue or submit a pull request.
@ -165,4 +165,4 @@ Our team creates other learning materials! Check out:
---
**Disclaimer**:
This document has been translated using the AI translation service [Co-op Translator](https://github.com/Azure/co-op-translator). While we aim for accuracy, please note that automated translations may include errors or inaccuracies. The original document in its native language should be regarded as the authoritative source. For critical information, professional human translation is advised. We are not responsible for any misunderstandings or misinterpretations resulting from the use of this translation.
This document has been translated using the AI translation service [Co-op Translator](https://github.com/Azure/co-op-translator). While we strive for accuracy, please note that automated translations may contain errors or inaccuracies. The original document in its native language should be regarded as the authoritative source. For critical information, professional human translation is recommended. We are not responsible for any misunderstandings or misinterpretations resulting from the use of this translation.

62
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@ -1,8 +1,8 @@
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@ -23,7 +23,7 @@ CO_OP_TRANSLATOR_METADATA:
# Inteligencia Artificial para Principiantes - Un Currículo
|![Sketchnote por @girlie_mac https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|![Sketchnote por @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.es.png)|
|:---:|
| AI Para Principiantes - _Sketchnote por [@girlie_mac](https://twitter.com/girlie_mac)_ |
@ -48,17 +48,17 @@ En este currículo, aprenderás:
* Diferentes enfoques de la Inteligencia Artificial, incluyendo el enfoque simbólico "tradicional" con **Representación del Conocimiento** y razonamiento ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Redes Neuronales** y **Aprendizaje Profundo**, que son el núcleo de la IA moderna. Ilustraremos los conceptos detrás de estos temas importantes utilizando código en dos de los marcos más populares: [TensorFlow](http://Tensorflow.org) y [PyTorch](http://pytorch.org).
* **Arquitecturas Neuronales** para trabajar con imágenes y texto. Cubriremos modelos recientes, aunque puede que no incluyamos lo más avanzado.
* **Arquitecturas Neuronales** para trabajar con imágenes y texto. Cubriremos modelos recientes, aunque puede que falte algo de lo más avanzado.
* Enfoques menos populares de IA, como **Algoritmos Genéticos** y **Sistemas Multi-Agente**.
Lo que no cubriremos en este currículo:
> [Encuentra todos los recursos adicionales para este curso en nuestra colección de Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Casos de negocio sobre el uso de **IA en Negocios**. Considera tomar el camino de aprendizaje [Introducción a la IA para usuarios empresariales](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) en Microsoft Learn, o [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), desarrollado en cooperación con [INSEAD](https://www.insead.edu/).
* Casos de negocio sobre el uso de **IA en Negocios**. Considera tomar el camino de aprendizaje [Introducción a la IA para usuarios de negocios](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) en Microsoft Learn, o [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), desarrollado en cooperación con [INSEAD](https://www.insead.edu/).
* **Aprendizaje Automático Clásico**, que está bien descrito en nuestro [Currículo de Aprendizaje Automático para Principiantes](http://github.com/Microsoft/ML-for-Beginners).
* Aplicaciones prácticas de IA construidas utilizando **[Servicios Cognitivos](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Para esto, recomendamos comenzar con los módulos de Microsoft Learn para [visión](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [procesamiento de lenguaje natural](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[IA Generativa con Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** y otros.
* Marcos específicos de ML en la **Nube**, como [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), o [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Considera usar los caminos de aprendizaje [Construir y operar soluciones de aprendizaje automático con Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) y [Construir y operar soluciones de aprendizaje automático con Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* Marcos específicos de ML **en la Nube**, como [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), o [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Considera usar los caminos de aprendizaje [Construir y operar soluciones de aprendizaje automático con Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) y [Construir y operar soluciones de aprendizaje automático con Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **IA Conversacional** y **Chat Bots**. Hay un camino de aprendizaje separado [Crear soluciones de IA conversacional](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), y también puedes consultar [esta publicación de blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) para más detalles.
* **Matemáticas profundas** detrás del aprendizaje profundo. Para esto, recomendamos [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) por Ian Goodfellow, Yoshua Bengio y Aaron Courville, que también está disponible en línea en [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
@ -77,55 +77,55 @@ Para una introducción sencilla a los temas de _IA en la Nube_, puedes considera
| 03 | [Perceptrón](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Laboratorio](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Perceptrón Multicapa y Creación de nuestro propio Marco](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Laboratorio](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Introducción a Frameworks (PyTorch/TensorFlow) y Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorio](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Visión por Computadora**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Explora Visión por Computadora en Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| IV | [**Visión por Computadora**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Explorar Visión por Computadora en Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Introducción a Visión por Computadora. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Laboratorio](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Redes Neuronales Convolucionales](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Arquitecturas CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Laboratorio](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Redes Pre-entrenadas y Aprendizaje por Transferencia](./lessons/4-ComputerVision/08-TransferLearning/README.md) y [Trucos de Entrenamiento](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorio](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 08 | [Redes Pre-entrenadas y Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) y [Trucos de Entrenamiento](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorio](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoders y VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Redes Generativas Adversarias y Transferencia de Estilo Artístico](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 10 | [Redes Generativas Antagónicas y Transferencia de Estilo Artístico](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Detección de Objetos](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Laboratorio](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Segmentación Semántica. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Procesamiento de Lenguaje Natural**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Explora Procesamiento de Lenguaje Natural en Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Representación de Texto. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embeddings semánticos de palabras. Word2Vec y GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelado de Lenguaje. Entrenando tus propios embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratorio](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Redes Neuronales Recurrentes](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Redes Recurrentes Generativas](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Laboratorio](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Reconocimiento de Entidades Nombradas](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratorio](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Modelos de Lenguaje Grandes, Programación de Prompts y Tareas de Few-Shot](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**Procesamiento de Lenguaje Natural**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Explorar Procesamiento de Lenguaje Natural en Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Representación de Texto. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embeddings Semánticos de Palabras. Word2Vec y GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelado de Lenguaje. Entrenando tus propios embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratorio](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Redes Neuronales Recurrentes](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Redes Recurrentes Generativas](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Laboratorio](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Reconocimiento de Entidades Nombradas](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratorio](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Modelos de Lenguaje Grandes, Programación con Prompts y Tareas de Pocos Ejemplos](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Otras Técnicas de IA** || |
| 21 | [Algoritmos Genéticos](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Aprendizaje por Refuerzo Profundo](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Laboratorio](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Sistemas Multi-Agente](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Ética en IA** | | |
| 24 | [Ética en IA y IA Responsable](./lessons/7-Ethics/README.md) | [Microsoft Learn: Principios de IA Responsable](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| VII | **Ética en la IA** | | |
| 24 | [Ética en la IA y IA Responsable](./lessons/7-Ethics/README.md) | [Microsoft Learn: Principios de IA Responsable](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Extras** | | |
| 25 | [Redes Multi-Modales, CLIP y VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Cada lección contiene
* Material de lectura previa
* Jupyter Notebooks ejecutables, que suelen ser específicos para el framework (**PyTorch** o **TensorFlow**). El notebook ejecutable también incluye mucho material teórico, por lo que para entender el tema necesitas revisar al menos una versión del notebook (ya sea PyTorch o TensorFlow).
* **Laboratorios** disponibles para algunos temas, que te dan la oportunidad de aplicar el material que has aprendido a un problema específico.
* Notebooks ejecutables de Jupyter, que a menudo son específicos para el framework (**PyTorch** o **TensorFlow**). El notebook ejecutable también incluye mucho material teórico, por lo que para entender el tema es necesario revisar al menos una versión del notebook (ya sea PyTorch o TensorFlow).
* **Laboratorios** disponibles para algunos temas, que te dan la oportunidad de aplicar el material aprendido a un problema específico.
* Algunas secciones contienen enlaces a módulos de [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) que cubren temas relacionados.
## Comenzando
- Hemos creado una [lección de configuración](./lessons/0-course-setup/setup.md) para ayudarte a configurar tu entorno de desarrollo. - Para educadores, también hemos creado una [lección de configuración de currículum](./lessons/0-course-setup/for-teachers.md).
- Cómo [Ejecutar el código en VSCode o Codepace](./lessons/0-course-setup/how-to-run.md)
- Cómo [Ejecutar el código en VSCode o CodeSpace](./lessons/0-course-setup/how-to-run.md)
Sigue estos pasos:
Haz un Fork del repositorio: Haz clic en el botón "Fork" en la esquina superior derecha de esta página.
Haz un Fork del Repositorio: Haz clic en el botón "Fork" en la esquina superior derecha de esta página.
Clona el repositorio: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Clona el Repositorio: `git clone https://github.com/microsoft/AI-For-Beginners.git`
No olvides darle una estrella (🌟) a este repositorio para encontrarlo más fácilmente más tarde.
## Conoce a otros estudiantes
Únete a nuestro [servidor oficial de Discord de IA](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) para conocer y conectarte con otros estudiantes que están tomando este curso y obtener apoyo.
Únete a nuestro [servidor oficial de Discord de IA](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) para conocer y conectar con otros estudiantes que están tomando este curso y obtener soporte.
Si tienes comentarios sobre el producto o preguntas mientras construyes, visita nuestro [Foro de Desarrolladores de Azure AI Foundry](https://aka.ms/foundry/forum)
@ -133,7 +133,7 @@ Si tienes comentarios sobre el producto o preguntas mientras construyes, visita
> **Una nota sobre los cuestionarios**: Todos los cuestionarios están contenidos en la carpeta Quiz-app en etc\quiz-app, o [En línea aquí](https://ff-quizzes.netlify.app/). Están vinculados desde dentro de las lecciones. La aplicación de cuestionarios puede ejecutarse localmente o desplegarse en Azure; sigue las instrucciones en la carpeta `quiz-app`. Se están localizando gradualmente.
## Se Busca Ayuda
¿Tienes sugerencias o encontraste errores ortográficos o de código? Crea un issue o un pull request.
¿Tienes sugerencias o encontraste errores de ortografía o en el código? Crea un issue o un pull request.
## Agradecimientos Especiales
@ -141,11 +141,11 @@ Si tienes comentarios sobre el producto o preguntas mientras construyes, visita
* **🔥 Editora:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustradora de Sketchnotes:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Creadora de Cuestionarios:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Contribuidores Principales:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **🙏 Contribuyentes Principales:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Otros Currículos
## Otros Planes de Estudio
¡Nuestro equipo produce otros currículos! Échales un vistazo:
¡Nuestro equipo produce otros planes de estudio! Échales un vistazo:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
@ -165,4 +165,4 @@ Si tienes comentarios sobre el producto o preguntas mientras construyes, visita
---
**Descargo de responsabilidad**:
Este documento ha sido traducido utilizando el servicio de traducción automática [Co-op Translator](https://github.com/Azure/co-op-translator). Aunque nos esforzamos por garantizar la precisión, tenga en cuenta que las traducciones automatizadas pueden contener errores o imprecisiones. El documento original en su idioma nativo debe considerarse como la fuente autorizada. Para información crítica, se recomienda una traducción profesional realizada por humanos. No nos hacemos responsables de malentendidos o interpretaciones erróneas que puedan surgir del uso de esta traducción.
Este documento ha sido traducido utilizando el servicio de traducción automática [Co-op Translator](https://github.com/Azure/co-op-translator). Si bien nos esforzamos por lograr precisión, tenga en cuenta que las traducciones automáticas pueden contener errores o imprecisiones. El documento original en su idioma nativo debe considerarse como la fuente autorizada. Para información crítica, se recomienda una traducción profesional realizada por humanos. No nos hacemos responsables de malentendidos o interpretaciones erróneas que puedan surgir del uso de esta traducción.

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@ -23,7 +23,7 @@ CO_OP_TRANSLATOR_METADATA:
# هوش مصنوعی برای مبتدیان - یک برنامه آموزشی
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.fa.png)|
|:---:|
| هوش مصنوعی برای مبتدیان - _طرح‌نگاری توسط [@girlie_mac](https://twitter.com/girlie_mac)_ |
@ -35,7 +35,7 @@ CO_OP_TRANSLATOR_METADATA:
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](./README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**اگر می‌خواهید زبان‌های ترجمه اضافی پشتیبانی شوند، لیست زبان‌های موجود [اینجا](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) قرار دارد.**
**اگر می‌خواهید زبان‌های ترجمه اضافی پشتیبانی شوند، لیست زبان‌های موجود [اینجا](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) قابل مشاهده است.**
## به جامعه بپیوندید
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -55,14 +55,14 @@ CO_OP_TRANSLATOR_METADATA:
> [تمام منابع اضافی این دوره را در مجموعه Microsoft Learn ما پیدا کنید](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* موارد تجاری استفاده از **هوش مصنوعی در تجارت**. پیشنهاد می‌کنیم مسیر یادگیری [مقدمه‌ای بر هوش مصنوعی برای کاربران تجاری](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) در Microsoft Learn یا [مدرسه کسب‌وکار هوش مصنوعی](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) که با همکاری [INSEAD](https://www.insead.edu/) توسعه یافته است، را دنبال کنید.
* موارد تجاری استفاده از **هوش مصنوعی در کسب‌وکار**. پیشنهاد می‌کنیم مسیر یادگیری [مقدمه‌ای بر هوش مصنوعی برای کاربران کسب‌وکار](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) در Microsoft Learn یا [مدرسه کسب‌وکار هوش مصنوعی](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) که با همکاری [INSEAD](https://www.insead.edu/) توسعه یافته است را دنبال کنید.
* **یادگیری ماشین کلاسیک** که به‌خوبی در برنامه آموزشی [یادگیری ماشین برای مبتدیان](http://github.com/Microsoft/ML-for-Beginners) توضیح داده شده است.
* کاربردهای عملی هوش مصنوعی که با استفاده از **[خدمات شناختی](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** ساخته شده‌اند. برای این موضوع، پیشنهاد می‌کنیم با ماژول‌های Microsoft Learn برای [بینایی](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)، [پردازش زبان طبیعی](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)، **[هوش مصنوعی مولد با سرویس Azure OpenAI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** و دیگر موارد شروع کنید.
* چارچوب‌های ابری خاص یادگیری ماشین، مانند [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)، [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)، یا [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). پیشنهاد می‌کنیم مسیرهای یادگیری [ساخت و اجرای راه‌حل‌های یادگیری ماشین با Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) و [ساخت و اجرای راه‌حل‌های یادگیری ماشین با Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) را دنبال کنید.
* **هوش مصنوعی مکالمه‌ای** و **چت‌بات‌ها**. یک مسیر یادگیری جداگانه [ایجاد راه‌حل‌های هوش مصنوعی مکالمه‌ای](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) وجود دارد و همچنین می‌توانید به [این پست وبلاگ](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) برای جزئیات بیشتر مراجعه کنید.
* **ریاضیات عمیق** پشت یادگیری عمیق. برای این موضوع، پیشنهاد می‌کنیم کتاب [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) نوشته Ian Goodfellow، Yoshua Bengio و Aaron Courville را مطالعه کنید که به‌صورت آنلاین نیز در دسترس است [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
برای یک معرفی ملایم به موضوعات _هوش مصنوعی در ابر_، می‌توانید مسیر یادگیری [شروع با هوش مصنوعی در Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) را دنبال کنید.
برای یک مقدمه ملایم به موضوعات _هوش مصنوعی در ابر_، می‌توانید مسیر یادگیری [شروع با هوش مصنوعی در Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) را دنبال کنید.
# محتوا
@ -74,26 +74,26 @@ CO_OP_TRANSLATOR_METADATA:
| II | **هوش مصنوعی نمادین** |
| 02 | [نمایش دانش و سیستم‌های خبره](./lessons/2-Symbolic/README.md) | [سیستم‌های خبره](./lessons/2-Symbolic/Animals.ipynb) / [هستی‌شناسی](./lessons/2-Symbolic/FamilyOntology.ipynb) /[گراف مفهومی](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**مقدمه‌ای بر شبکه‌های عصبی**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [پرسپترون](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [دفترچه یادداشت](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [آزمایشگاه](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [پرسپترون چندلایه و ایجاد چارچوب خودمان](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [دفترچه یادداشت](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [آزمایشگاه](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 03 | [پرسیپترون](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [دفترچه یادداشت](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [آزمایشگاه](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [پرسیپترون چندلایه و ایجاد چارچوب خودمان](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [دفترچه یادداشت](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [آزمایشگاه](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [مقدمه‌ای بر چارچوب‌ها (PyTorch/TensorFlow) و بیش‌برازش](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [آزمایشگاه](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**بینایی کامپیوتر**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [کاوش بینایی کامپیوتر در Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [مقدمه‌ای بر بینایی کامپیوتر. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [دفترچه یادداشت](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [آزمایشگاه](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [شبکه‌های عصبی کانولوشنی](./lessons/4-ComputerVision/07-ConvNets/README.md) و [معماری‌های CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [آزمایشگاه](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 07 | [شبکه‌های عصبی پیچشی](./lessons/4-ComputerVision/07-ConvNets/README.md) و [معماری‌های CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [آزمایشگاه](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [شبکه‌های از پیش آموزش‌دیده و یادگیری انتقالی](./lessons/4-ComputerVision/08-TransferLearning/README.md) و [ترفندهای آموزشی](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [آزمایشگاه](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [خودرمزگذارها و VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [شبکه‌های مولد متخاصم و انتقال سبک هنری](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [تشخیص اشیا](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [آزمایشگاه](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [تقسیم‌بندی معنایی. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**پردازش زبان طبیعی**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [کاوش پردازش زبان طبیعی در Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 13 | [نمایش متن. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [تعبیه معنایی کلمات. Word2Vec و GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [مدل‌سازی زبان. آموزش تعبیه‌های خودتان](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [آزمایشگاه](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [شبکه‌های عصبی بازگشتی](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [شبکه‌های بازگشتی مولد](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [آزمایشگاه](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ترانسفورمرها. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [تشخیص موجودیت‌های نام‌دار](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [آزمایشگاه](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [مدل‌های زبان بزرگ، برنامه‌نویسی با پرامپت و وظایف کم‌شات](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [نمایش متن. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [تعبیه معنایی کلمات. Word2Vec و GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [مدل‌سازی زبان. آموزش تعبیه‌های خودتان](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [آزمایشگاه](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [شبکه‌های عصبی بازگشتی](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [شبکه‌های بازگشتی مولد](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [آزمایشگاه](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ترانسفورمرها. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [تشخیص موجودیت‌های نام‌دار](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [آزمایشگاه](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [مدل‌های زبانی بزرگ، برنامه‌نویسی با دستورات و وظایف کم‌شات](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **سایر تکنیک‌های هوش مصنوعی** || |
| 21 | [الگوریتم‌های ژنتیکی](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [دفترچه یادداشت](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [یادگیری تقویتی عمیق](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) / [TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [آزمایشگاه](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -106,7 +106,7 @@ CO_OP_TRANSLATOR_METADATA:
## هر درس شامل موارد زیر است
* مطالب پیش‌خوانی
* دفترچه‌های یادداشت اجرایی Jupyter، که اغلب مختص چارچوب (**PyTorch** یا **TensorFlow**) هستند. این دفترچه‌های اجرایی همچنین شامل مطالب نظری زیادی هستند، بنابراین برای درک موضوع باید حداقل یکی از نسخه‌های دفترچه یادداشت (PyTorch یا TensorFlow) را مرور کنید.
* دفترچه‌های یادداشت Jupyter قابل اجرا که اغلب مختص چارچوب (**PyTorch** یا **TensorFlow**) هستند. این دفترچه‌ها همچنین شامل مطالب نظری زیادی هستند، بنابراین برای درک موضوع باید حداقل یکی از نسخه‌های دفترچه یادداشت (PyTorch یا TensorFlow) را مرور کنید.
* **آزمایشگاه‌ها** که برای برخی موضوعات در دسترس هستند و به شما فرصت می‌دهند تا مطالبی که یاد گرفته‌اید را روی یک مسئله خاص اعمال کنید.
* برخی بخش‌ها شامل لینک‌هایی به ماژول‌های [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) هستند که موضوعات مرتبط را پوشش می‌دهند.
@ -118,20 +118,20 @@ CO_OP_TRANSLATOR_METADATA:
مراحل زیر را دنبال کنید:
مخزن را Fork کنید: روی دکمه "Fork" در گوشه بالا-راست این صفحه کلیک کنید.
مخزن را فورک کنید: روی دکمه "Fork" در گوشه بالا-راست این صفحه کلیک کنید.
مخزن را Clone کنید: `git clone https://github.com/microsoft/AI-For-Beginners.git`
مخزن را کلون کنید: `git clone https://github.com/microsoft/AI-For-Beginners.git`
فراموش نکنید که این مخزن را ستاره‌دار کنید (🌟) تا بعداً راحت‌تر آن را پیدا کنید.
فراموش نکنید که این مخزن را ستاره‌دار (🌟) کنید تا بعداً راحت‌تر آن را پیدا کنید.
## ملاقات با سایر یادگیرندگان
به [سرور رسمی دیسکورد هوش مصنوعی](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) ما بپیوندید تا با سایر یادگیرندگان این دوره ملاقات کنید، شبکه‌سازی کنید و پشتیبانی دریافت کنید.
به [سرور رسمی دیسکورد هوش مصنوعی](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) ما بپیوندید تا با سایر یادگیرندگان این دوره ملاقات کنید و شبکه‌سازی کنید و پشتیبانی دریافت کنید.
اگر بازخورد محصول یا سوالاتی در حین ساخت دارید، به [فروم توسعه‌دهندگان Azure AI Foundry](https://aka.ms/foundry/forum) ما مراجعه کنید.
اگر بازخورد محصول یا سوالاتی در حین ساخت دارید، به [انجمن توسعه‌دهندگان Azure AI Foundry](https://aka.ms/foundry/forum) مراجعه کنید.
## آزمون‌ها
> **توضیحی درباره آزمون‌ها**: تمامی آزمون‌ها در پوشه Quiz-app در مسیر etc\quiz-app قرار دارند، یا [به صورت آنلاین اینجا](https://ff-quizzes.netlify.app/). این آزمون‌ها از داخل درس‌ها لینک شده‌اند. برنامه آزمون می‌تواند به صورت محلی اجرا شود یا در Azure مستقر شود؛ دستورالعمل‌های موجود در پوشه `quiz-app` را دنبال کنید. این آزمون‌ها به تدریج بومی‌سازی می‌شوند.
> **توضیحی درباره آزمون‌ها**: تمامی آزمون‌ها در پوشه Quiz-app در مسیر etc\quiz-app قرار دارند، یا [به صورت آنلاین اینجا](https://ff-quizzes.netlify.app/) موجود هستند. این آزمون‌ها از داخل درس‌ها لینک شده‌اند. اپلیکیشن آزمون می‌تواند به صورت محلی اجرا شود یا در Azure مستقر شود؛ دستورالعمل‌های موجود در پوشه `quiz-app` را دنبال کنید. این آزمون‌ها به تدریج در حال بومی‌سازی هستند.
## درخواست کمک
آیا پیشنهادی دارید یا خطاهای املایی یا کدی پیدا کرده‌اید؟ یک issue ایجاد کنید یا یک pull request ارسال کنید.
@ -148,22 +148,22 @@ CO_OP_TRANSLATOR_METADATA:
تیم ما دوره‌های دیگری نیز تولید می‌کند! بررسی کنید:
- [هوش مصنوعی مولد برای مبتدیان](https://aka.ms/genai-beginners)
- [هوش مصنوعی مولد برای مبتدیان .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [هوش مصنوعی مولد با جاوااسکریپت](https://github.com/microsoft/generative-ai-with-javascript)
- [هوش مصنوعی مولد با جاوا](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [هوش مصنوعی برای مبتدیان](https://aka.ms/ai-beginners)
- [علم داده برای مبتدیان](https://aka.ms/datascience-beginners)
- [یادگیری ماشین برای مبتدیان](https://aka.ms/ml-beginners)
- [امنیت سایبری برای مبتدیان](https://github.com/microsoft/Security-101)
- [توسعه وب برای مبتدیان](https://aka.ms/webdev-beginners)
- [اینترنت اشیا برای مبتدیان](https://aka.ms/iot-beginners)
- [توسعه XR برای مبتدیان](https://github.com/microsoft/xr-development-for-beginners)
- [تسلط بر GitHub Copilot برای استفاده عامل‌محور](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [تسلط بر GitHub Copilot برای توسعه‌دهندگان C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [ماجراجویی Copilot خود را انتخاب کنید](https://github.com/microsoft/CopilotAdventures)
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---
**سلب مسئولیت**:
این سند با استفاده از سرویس ترجمه هوش مصنوعی [Co-op Translator](https://github.com/Azure/co-op-translator) ترجمه شده است. در حالی که ما تلاش می‌کنیم دقت را حفظ کنیم، لطفاً توجه داشته باشید که ترجمه‌های خودکار ممکن است شامل خطاها یا نادرستی‌ها باشند. سند اصلی به زبان اصلی آن باید به عنوان منبع معتبر در نظر گرفته شود. برای اطلاعات حساس، توصیه می‌شود از ترجمه حرفه‌ای انسانی استفاده کنید. ما مسئولیتی در قبال سوء تفاهم‌ها یا تفسیرهای نادرست ناشی از استفاده از این ترجمه نداریم.
این سند با استفاده از سرویس ترجمه هوش مصنوعی [Co-op Translator](https://github.com/Azure/co-op-translator) ترجمه شده است. در حالی که ما برای دقت تلاش می‌کنیم، لطفاً توجه داشته باشید که ترجمه‌های خودکار ممکن است شامل خطاها یا نادرستی‌هایی باشند. سند اصلی به زبان اصلی آن باید به عنوان منبع معتبر در نظر گرفته شود. برای اطلاعات حساس، ترجمه حرفه‌ای انسانی توصیه می‌شود. ما هیچ مسئولیتی در قبال سوءتفاهم‌ها یا تفسیرهای نادرست ناشی از استفاده از این ترجمه نداریم.

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@ -47,7 +47,7 @@ Tutustu **tekoälyn** (AI) maailmaan 12 viikon ja 24 oppitunnin opetussuunnitelm
Tässä opetussuunnitelmassa opit:
* Erilaisia lähestymistapoja tekoälyyn, mukaan lukien "vanha kunnon" symbolinen lähestymistapa **tiedon esittämiseen** ja päättelyyn ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neuroverkot** ja **syväoppiminen**, jotka ovat modernin tekoälyn ytimessä. Havainnollistamme näitä tärkeitä aiheita koodin avulla kahdessa suosituimmassa kehikossa - [TensorFlow](http://Tensorflow.org) ja [PyTorch](http://pytorch.org).
* **Neuroverkot** ja **syväoppiminen**, jotka ovat modernin tekoälyn ytimessä. Havainnollistamme näitä tärkeitä aiheita koodin avulla kahdessa suosituimmassa kehitysalustassa - [TensorFlow](http://Tensorflow.org) ja [PyTorch](http://pytorch.org).
* **Neuroarkkitehtuurit** kuvien ja tekstin käsittelyyn. Käymme läpi viimeaikaisia malleja, mutta emme välttämättä kata aivan uusinta huipputeknologiaa.
* Vähemmän tunnettuja tekoälymenetelmiä, kuten **geneettiset algoritmit** ja **moniagenttijärjestelmät**.
@ -55,14 +55,14 @@ Mitä emme käsittele tässä opetussuunnitelmassa:
> [Löydä kaikki lisäresurssit tähän kurssiin Microsoft Learn -kokoelmastamme](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **Tekoälyn liiketoimintatapaukset**. Suosittelemme ottamaan [Johdatus tekoälyyn liiketoiminnan käyttäjille](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) oppimispolun Microsoft Learnissa tai [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), joka on kehitetty yhteistyössä [INSEAD](https://www.insead.edu/) kanssa.
* **Tekoälyn liiketoimintatapaukset**. Suosittelemme tutustumaan [Johdatus tekoälyyn liiketoiminnan käyttäjille](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) -oppimispolkuun Microsoft Learnissa tai [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), joka on kehitetty yhteistyössä [INSEAD](https://www.insead.edu/):n kanssa.
* **Klassinen koneoppiminen**, joka on hyvin kuvattu [Koneoppiminen aloittelijoille -opetussuunnitelmassamme](http://github.com/Microsoft/ML-for-Beginners).
* Käytännön tekoälysovellukset, jotka on rakennettu **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** avulla. Suosittelemme aloittamaan Microsoft Learnin moduuleilla [näkö](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [luonnollinen kielenkäsittely](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generatiivinen tekoäly Azure OpenAI -palvelulla](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** ja muut.
* Tietyt ML **pilvikehykset**, kuten [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) tai [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Suosittelemme oppimispolkuja [Rakenna ja operoi koneoppimisratkaisuja Azure Machine Learningilla](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) ja [Rakenna ja operoi koneoppimisratkaisuja Azure Databricksilla](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* Käytännön tekoälysovellukset, jotka on rakennettu **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** avulla. Suosittelemme aloittamaan Microsoft Learnin moduuleista, kuten [näkö](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [luonnollisen kielen käsittely](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generatiivinen tekoäly Azure OpenAI -palvelulla](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** ja muut.
* Tietyt ML **pilvialustat**, kuten [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) tai [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Suosittelemme oppimispolkuja [Rakenna ja käytä koneoppimisratkaisuja Azure Machine Learningilla](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) ja [Rakenna ja käytä koneoppimisratkaisuja Azure Databricksilla](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Keskustelu-AI** ja **chatbotit**. Erillinen oppimispolku löytyy [Luo keskustelu-AI-ratkaisuja](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), ja voit myös viitata [tähän blogikirjoitukseen](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) saadaksesi lisätietoja.
* **Syvä matematiikka** syväoppimisen taustalla. Suosittelemme Ian Goodfellowin, Yoshua Bengion ja Aaron Courvillen kirjaa [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618), joka on saatavilla myös verkossa osoitteessa [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Jos haluat lempeän johdannon _tekoäly pilvessä_ -aiheisiin, harkitse oppimispolkua [Aloita tekoälyllä Azurella](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
Jos haluat lempeän johdannon _tekoäly pilvessä_ -aiheisiin, harkitse oppimispolkua [Aloita tekoälyllä Azure-alustalla](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Sisältö
@ -75,39 +75,39 @@ Jos haluat lempeän johdannon _tekoäly pilvessä_ -aiheisiin, harkitse oppimisp
| 02 | [Tiedon esittäminen ja asiantuntijajärjestelmät](./lessons/2-Symbolic/README.md) | [Asiantuntijajärjestelmät](./lessons/2-Symbolic/Animals.ipynb) / [Ontologia](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Käsitekaavio](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Johdatus neuroverkkoihin**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Monikerroksinen perceptron ja oman kehikon luominen](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Johdanto kehyksiin (PyTorch/TensorFlow) ja yliohjautumiseen](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Labra](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| 04 | [Monikerroksinen perceptron ja oman kehitysalustan luominen](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Johdanto kehyksiin (PyTorch/TensorFlow) ja yliohjautumiseen](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Tietokonenäkö**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Tutustu tietokonenäköön Microsoft Azuren avulla](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Johdanto tietokonenäköön. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Muistikirja](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Labra](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvoluutioneuroverkot](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN-arkkitehtuurit](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Labra](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Esikoulutetut verkot ja siirto-oppiminen](./lessons/4-ComputerVision/08-TransferLearning/README.md) ja [Koulutusvinkit](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Labra](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 06 | [Johdanto tietokonenäköön. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvoluutioneuroverkot](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN-arkkitehtuurit](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Esikoulutetut verkot ja siirto-oppiminen](./lessons/4-ComputerVision/08-TransferLearning/README.md) ja [Koulutusvinkit](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autokooderit ja VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generatiiviset vastakkaisverkot ja taiteellinen tyylinsiirto](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Kohteentunnistus](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Labra](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 11 | [Kohteentunnistus](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semanttinen segmentointi. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Luonnollisen kielen käsittely**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Tutustu luonnollisen kielen käsittelyyn Microsoft Azuren avulla](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Tekstin esitystavat. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semanttiset sanavektorit. Word2Vec ja GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Kielimallinnus. Omien sanavektorien kouluttaminen](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Labra](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Toistuvat neuroverkot](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatiiviset toistuvat verkot](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Labra](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformerit. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Nimeämisen tunnistus](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Labra](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Suuret kielimallit, kehotteiden ohjelmointi ja vähäisten esimerkkien tehtävät](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Tekstin esitystavat. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semanttiset sanavektorit. Word2Vec ja GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Kielimallinnus. Omien sanavektorien kouluttaminen](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Toistuvat neuroverkot](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatiiviset toistuvat verkot](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformerit. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Nimekkäiden entiteettien tunnistus](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Suuret kielimallit, kehotteiden ohjelmointi ja vähäisten esimerkkien tehtävät](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Muut tekoälytekniikat** || |
| 21 | [Geneettiset algoritmit](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Muistikirja](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Syvä vahvistusoppiminen](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Labra](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 21 | [Geneettiset algoritmit](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Syvä vahvistusoppiminen](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Moniagenttijärjestelmät](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Tekoälyn etiikka** | | |
| 24 | [Tekoälyn etiikka ja vastuullinen tekoäly](./lessons/7-Ethics/README.md) | [Microsoft Learn: Vastuullisen tekoälyn periaatteet](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Lisämateriaali** | | |
| 25 | [Monimodaaliset verkot, CLIP ja VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Muistikirja](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 25 | [Monimodaaliset verkot, CLIP ja VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Jokainen oppitunti sisältää
* Ennakkolukemista
* Suoritettavia Jupyter-muistikirjoja, jotka ovat usein kehyskohtaisia (**PyTorch** tai **TensorFlow**). Suoritettavat muistikirjat sisältävät myös paljon teoreettista materiaalia, joten aiheen ymmärtämiseksi sinun tulee käydä läpi ainakin yksi muistikirjaversio (joko PyTorch tai TensorFlow).
* **Labroja**, jotka ovat saatavilla joillekin aiheille ja antavat mahdollisuuden soveltaa oppimaasi tiettyyn ongelmaan.
* Suoritettavia Jupyter Notebookeja, jotka ovat usein kehyskohtaisia (**PyTorch** tai **TensorFlow**). Suoritettava notebook sisältää myös paljon teoreettista materiaalia, joten aiheen ymmärtämiseksi sinun tulee käydä läpi vähintään yksi versio notebookista (joko PyTorch tai TensorFlow).
* **Lab-tehtäviä**, jotka ovat saatavilla joillekin aiheille ja antavat mahdollisuuden soveltaa oppimaasi tiettyyn ongelmaan.
* Joissakin osioissa on linkkejä [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) -moduuleihin, jotka käsittelevät aiheeseen liittyviä teemoja.
## Aloittaminen
@ -117,52 +117,52 @@ Jos haluat lempeän johdannon _tekoäly pilvessä_ -aiheisiin, harkitse oppimisp
Seuraa näitä vaiheita:
Haarauta arkisto: Klikkaa tämän sivun oikeassa yläkulmassa olevaa "Fork"-painiketta.
Haarauta repositorio: Klikkaa tämän sivun oikeassa yläkulmassa olevaa "Fork"-painiketta.
Kloonaa arkisto: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Kloonaa repositorio: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Älä unohda tähdittää (🌟) tätä arkistoa, jotta löydät sen helpommin myöhemmin.
Älä unohda tähdittää (🌟) tätä repositoriota, jotta löydät sen helpommin myöhemmin.
## Tapaa muita oppijoita
Liity [viralliselle AI Discord-palvelimellemme](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) tavataksesi ja verkostoituaksesi muiden kurssin oppijoiden kanssa ja saadaksesi tukea.
Liity [viralliselle AI Discord-palvelimellemme](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) tavataksesi ja verkostoituaksesi muiden kurssin oppijoiden kanssa sekä saadaksesi tukea.
Jos sinulla on palautetta tuotteesta tai kysymyksiä rakentamisen aikana, käy [Azure AI Foundry Developer Forumilla](https://aka.ms/foundry/forum)
## Kyselyt
> **Huomio tietovisoista**: Kaikki tietovisat löytyvät Quiz-app-kansiosta polusta etc\quiz-app, tai [Verkossa Täällä](https://ff-quizzes.netlify.app/). Ne on linkitetty oppituntien sisällä, ja tietovisasovellusta voi käyttää paikallisesti tai julkaista Azureen; seuraa ohjeita `quiz-app`-kansiossa. Tietovisoja lokalisoidaan vähitellen.
> **Huomio visailuista**: Kaikki visailut löytyvät Quiz-app-kansiosta polusta etc\quiz-app, tai [Verkossa Täällä](https://ff-quizzes.netlify.app/). Ne on linkitetty oppituntien sisällä, ja visailusovellusta voi käyttää paikallisesti tai julkaista Azureen; seuraa ohjeita `quiz-app`-kansiossa. Niitä lokalisoidaan vähitellen.
## Apua kaivataan
Onko sinulla ehdotuksia tai oletko löytänyt kirjoitus- tai koodivirheitä? Luo issue tai tee pull request.
## Erityiskiitokset
* **✍️ Pääkirjoittaja:** [Dmitry Soshnikov](http://soshnikov.com), tohtori
* **🔥 Toimittaja:** [Jen Looper](https://twitter.com/jenlooper), tohtori
* **✍️ Pääkirjoittaja:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Toimittaja:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Sketchnote-kuvittaja:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Kysymysten laatija:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **✅ Visailun luoja:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Keskeiset avustajat:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Muut oppimateriaalit
## Muut opetusohjelmat
Tiimimme tuottaa myös muita oppimateriaaleja! Tutustu näihin:
Tiimimme tuottaa myös muita opetusohjelmia! Tutustu:
- [Generatiivinen tekoäly aloittelijoille](https://aka.ms/genai-beginners)
- [Generatiivinen tekoäly aloittelijoille .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generatiivinen tekoäly JavaScriptillä](https://github.com/microsoft/generative-ai-with-javascript)
- [Generatiivinen tekoäly Javalla](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [Tekoäly aloittelijoille](https://aka.ms/ai-beginners)
- [Generatiivinen AI aloittelijoille](https://aka.ms/genai-beginners)
- [Generatiivinen AI aloittelijoille .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generatiivinen AI JavaScriptillä](https://github.com/microsoft/generative-ai-with-javascript)
- [Generatiivinen AI Javalla](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI aloittelijoille](https://aka.ms/ai-beginners)
- [Data-analytiikka aloittelijoille](https://aka.ms/datascience-beginners)
- [Koneoppiminen aloittelijoille](https://aka.ms/ml-beginners)
- [Kyberturvallisuus aloittelijoille](https://github.com/microsoft/Security-101)
- [Web-kehitys aloittelijoille](https://aka.ms/webdev-beginners)
- [IoT aloittelijoille](https://aka.ms/iot-beginners)
- [XR-kehitys aloittelijoille](https://github.com/microsoft/xr-development-for-beginners)
- [GitHub Copilotin hallinta agenttikäyttöön](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [GitHub Copilotin hallinta agenttipohjaiseen käyttöön](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [GitHub Copilotin hallinta C#/.NET-kehittäjille](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Valitse oma Copilot-seikkailusi](https://github.com/microsoft/CopilotAdventures)
---
**Vastuuvapauslauseke**:
Tämä asiakirja on käännetty käyttämällä tekoälypohjaista käännöspalvelua [Co-op Translator](https://github.com/Azure/co-op-translator). Pyrimme tarkkuuteen, mutta huomioithan, että automaattiset käännökset voivat sisältää virheitä tai epätarkkuuksia. Alkuperäistä asiakirjaa sen alkuperäisellä kielellä tulee pitää ensisijaisena lähteenä. Kriittisen tiedon osalta suositellaan ammattimaista ihmiskääntämistä. Emme ole vastuussa tämän käännöksen käytöstä aiheutuvista väärinkäsityksistä tai virhetulkinnoista.
Tämä asiakirja on käännetty käyttämällä tekoälypohjaista käännöspalvelua [Co-op Translator](https://github.com/Azure/co-op-translator). Vaikka pyrimme tarkkuuteen, huomioithan, että automaattiset käännökset voivat sisältää virheitä tai epätarkkuuksia. Alkuperäinen asiakirja sen alkuperäisellä kielellä tulisi pitää ensisijaisena lähteenä. Kriittisen tiedon osalta suositellaan ammattimaista ihmiskäännöstä. Emme ole vastuussa väärinkäsityksistä tai virhetulkinnoista, jotka johtuvat tämän käännöksen käytöstä.

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@ -1,8 +1,8 @@
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[![Licence GitHub](https://img.shields.io/github/license/microsoft/AI-For-Beginners.svg)](https://github.com/microsoft/AI-For-Beginners/blob/main/LICENSE)
[![Contributeurs GitHub](https://img.shields.io/github/contributors/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/graphs/contributors/)
[![Problèmes GitHub](https://img.shields.io/github/issues/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/issues/)
[![Pull-requests GitHub](https://img.shields.io/github/issues-pr/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/pulls/)
[![Pull Requests GitHub](https://img.shields.io/github/issues-pr/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/pulls/)
[![PRs Bienvenus](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com)
[![Observateurs GitHub](https://img.shields.io/github/watchers/microsoft/AI-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/AI-For-Beginners/watchers/)
@ -23,15 +23,15 @@ CO_OP_TRANSLATOR_METADATA:
# Intelligence Artificielle pour Débutants - Un Programme
|![Sketchnote par @girlie_mac https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|![Sketchnote par @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.fr.png)|
|:---:|
| AI pour Débutants - _Sketchnote par [@girlie_mac](https://twitter.com/girlie_mac)_ |
| AI Pour Débutants - _Sketchnote par [@girlie_mac](https://twitter.com/girlie_mac)_ |
Explorez le monde de l'**Intelligence Artificielle** (IA) avec notre programme de 12 semaines et 24 leçons ! Il inclut des leçons pratiques, des quiz et des laboratoires. Ce programme est adapté aux débutants et couvre des outils comme TensorFlow et PyTorch, ainsi que des questions d'éthique en IA.
### 🌐 Support Multilingue
#### Supporté via GitHub Action (Automatisé & Toujours à Jour)
#### Supporté via GitHub Action (Automatisé et Toujours à Jour)
[Français](./README.md) | [Espagnol](../es/README.md) | [Allemand](../de/README.md) | [Russe](../ru/README.md) | [Arabe](../ar/README.md) | [Persan (Farsi)](../fa/README.md) | [Ourdou](../ur/README.md) | [Chinois (Simplifié)](../zh/README.md) | [Chinois (Traditionnel, Macao)](../mo/README.md) | [Chinois (Traditionnel, Hong Kong)](../hk/README.md) | [Chinois (Traditionnel, Taïwan)](../tw/README.md) | [Japonais](../ja/README.md) | [Coréen](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Népalais](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portugais (Portugal)](../pt/README.md) | [Portugais (Brésil)](../br/README.md) | [Italien](../it/README.md) | [Polonais](../pl/README.md) | [Turc](../tr/README.md) | [Grec](../el/README.md) | [Thaï](../th/README.md) | [Suédois](../sv/README.md) | [Danois](../da/README.md) | [Norvégien](../no/README.md) | [Finnois](../fi/README.md) | [Néerlandais](../nl/README.md) | [Hébreu](../he/README.md) | [Vietnamien](../vi/README.md) | [Indonésien](../id/README.md) | [Malais](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hongrois](../hu/README.md) | [Tchèque](../cs/README.md) | [Slovaque](../sk/README.md) | [Roumain](../ro/README.md) | [Bulgare](../bg/README.md) | [Serbe (Cyrillique)](../sr/README.md) | [Croate](../hr/README.md) | [Slovène](../sl/README.md) | [Ukrainien](../uk/README.md) | [Birman (Myanmar)](../my/README.md)
@ -47,20 +47,20 @@ Explorez le monde de l'**Intelligence Artificielle** (IA) avec notre programme d
Dans ce programme, vous apprendrez :
* Différentes approches de l'Intelligence Artificielle, y compris l'approche symbolique "classique" avec la **Représentation des Connaissances** et le raisonnement ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* Les **Réseaux Neuronaux** et le **Deep Learning**, qui sont au cœur de l'IA moderne. Nous illustrerons les concepts derrière ces sujets importants avec du code dans deux des frameworks les plus populaires - [TensorFlow](http://Tensorflow.org) et [PyTorch](http://pytorch.org).
* Les **Architectures Neuronales** pour travailler avec les images et le texte. Nous couvrirons des modèles récents, mais il se peut que nous manquions un peu des derniers modèles à la pointe.
* Les **Réseaux Neuronaux** et l'**Apprentissage Profond**, qui sont au cœur de l'IA moderne. Nous illustrerons les concepts derrière ces sujets importants avec du code dans deux des frameworks les plus populaires - [TensorFlow](http://Tensorflow.org) et [PyTorch](http://pytorch.org).
* Les **Architectures Neuronales** pour travailler avec les images et le texte. Nous couvrirons des modèles récents, mais il se peut que nous ne soyons pas totalement à jour avec les dernières avancées.
* Des approches moins populaires de l'IA, comme les **Algorithmes Génétiques** et les **Systèmes Multi-Agents**.
Ce que nous ne couvrirons pas dans ce programme :
> [Retrouvez toutes les ressources supplémentaires pour ce cours dans notre collection Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Les cas d'utilisation de l'**IA en Entreprise**. Pensez à suivre le parcours d'apprentissage [Introduction à l'IA pour les utilisateurs professionnels](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) sur Microsoft Learn, ou [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), développé en coopération avec [INSEAD](https://www.insead.edu/).
* Le **Machine Learning Classique**, qui est bien décrit dans notre programme [Machine Learning pour Débutants](http://github.com/Microsoft/ML-for-Beginners).
* Les cas d'utilisation de l'**IA en Entreprise**. Pensez à suivre le parcours d'apprentissage [Introduction à l'IA pour les utilisateurs professionnels](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) sur Microsoft Learn, ou [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), développé en collaboration avec [INSEAD](https://www.insead.edu/).
* L'**Apprentissage Automatique Classique**, qui est bien décrit dans notre programme [Machine Learning pour Débutants](http://github.com/Microsoft/ML-for-Beginners).
* Les applications pratiques de l'IA construites avec **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Pour cela, nous vous recommandons de commencer par les modules Microsoft Learn pour [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [traitement du langage naturel](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[IA Générative avec Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** et autres.
* Les **Frameworks Cloud ML** spécifiques, comme [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), ou [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Pensez à utiliser les parcours d'apprentissage [Créer et exploiter des solutions de machine learning avec Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) et [Créer et exploiter des solutions de machine learning avec Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* Les **Frameworks Cloud ML** spécifiques, comme [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), ou [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Pensez à utiliser les parcours d'apprentissage [Créer et exploiter des solutions d'apprentissage automatique avec Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) et [Créer et exploiter des solutions d'apprentissage automatique avec Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* L'**IA Conversationnelle** et les **Chat Bots**. Il existe un parcours d'apprentissage séparé [Créer des solutions d'IA conversationnelle](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), et vous pouvez également consulter [cet article de blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) pour plus de détails.
* Les **Mathématiques Approfondies** derrière le deep learning. Pour cela, nous vous recommandons [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) par Ian Goodfellow, Yoshua Bengio et Aaron Courville, également disponible en ligne à [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Les **Mathématiques Approfondies** derrière l'apprentissage profond. Pour cela, nous vous recommandons [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) par Ian Goodfellow, Yoshua Bengio et Aaron Courville, également disponible en ligne à [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Pour une introduction douce aux sujets _IA dans le Cloud_, vous pouvez envisager de suivre le parcours d'apprentissage [Commencer avec l'intelligence artificielle sur Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
@ -86,28 +86,28 @@ Pour une introduction douce aux sujets _IA dans le Cloud_, vous pouvez envisager
| 11 | [Détection d'objets](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Segmentation sémantique. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Traitement du langage naturel**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Explorer le traitement du langage naturel sur Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Représentation de texte. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embeddings sémantiques de mots. Word2Vec et GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modélisation de langage. Entraînez vos propres embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Réseaux neuronaux récurrents](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Réseaux récurrents génératifs](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Reconnaissance d'entités nommées](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Grands modèles de langage, programmation par prompts et tâches en apprentissage par petits échantillons](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Représentation de texte. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embeddings sémantiques de mots. Word2Vec et GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modélisation de langage. Entraînez vos propres embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Réseaux neuronaux récurrents](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Réseaux récurrents génératifs](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Reconnaissance d'entités nommées](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Grands modèles de langage, programmation par prompts et tâches en apprentissage par petits échantillons](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Autres techniques d'IA** || |
| 21 | [Algorithmes génétiques](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Apprentissage par renforcement profond](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Systèmes multi-agents](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Éthique de l'IA** | | |
| 24 | [Éthique de l'IA et IA responsable](./lessons/7-Ethics/README.md) | [Microsoft Learn : Principes de l'IA responsable](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| 24 | [Éthique de l'IA et IA responsable](./lessons/7-Ethics/README.md) | [Microsoft Learn : Principes d'IA responsable](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Extras** | | |
| 25 | [Réseaux multi-modaux, CLIP et VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Chaque leçon contient
* Matériel de pré-lecture
* Notebooks Jupyter exécutables, souvent spécifiques au framework (**PyTorch** ou **TensorFlow**). Le notebook exécutable contient également beaucoup de contenu théorique, donc pour comprendre le sujet, vous devez parcourir au moins une version du notebook (PyTorch ou TensorFlow).
* **Labs** disponibles pour certains sujets, qui vous permettent d'appliquer le contenu appris à un problème spécifique.
* Du matériel de pré-lecture
* Des notebooks Jupyter exécutables, souvent spécifiques au framework (**PyTorch** ou **TensorFlow**). Le notebook exécutable contient également beaucoup de contenu théorique, donc pour comprendre le sujet, vous devez parcourir au moins une version du notebook (PyTorch ou TensorFlow).
* **Labs** disponibles pour certains sujets, qui vous donnent l'opportunité d'appliquer le contenu appris à un problème spécifique.
* Certaines sections contiennent des liens vers des modules [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) qui couvrent des sujets connexes.
## Pour commencer
@ -121,48 +121,48 @@ Forkez le dépôt : Cliquez sur le bouton "Fork" en haut à droite de cette page
Clonez le dépôt : `git clone https://github.com/microsoft/AI-For-Beginners.git`
N'oubliez pas de mettre une étoile (🌟) à ce dépôt pour le retrouver plus facilement plus tard.
N'oubliez pas d'ajouter une étoile (🌟) à ce dépôt pour le retrouver plus facilement plus tard.
## Rencontrez d'autres apprenants
Rejoignez notre [serveur Discord officiel sur l'IA](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) pour rencontrer et échanger avec d'autres apprenants suivant ce cours et obtenir du soutien.
Rejoignez notre [serveur Discord officiel sur l'IA](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) pour rencontrer et réseauter avec d'autres apprenants suivant ce cours et obtenir du soutien.
Si vous avez des retours sur le produit ou des questions pendant la construction, visitez notre [forum des développeurs Azure AI Foundry](https://aka.ms/foundry/forum)
## Quiz
> **Une note à propos des quiz** : Tous les quiz se trouvent dans le dossier Quiz-app sous etc\quiz-app, ou [en ligne ici](https://ff-quizzes.netlify.app/). Ils sont liés depuis les leçons. L'application de quiz peut être exécutée localement ou déployée sur Azure ; suivez les instructions dans le dossier `quiz-app`. Leur localisation est en cours de réalisation progressivement.
> **Une note sur les quiz** : Tous les quiz se trouvent dans le dossier Quiz-app dans etc\quiz-app, ou [En ligne ici](https://ff-quizzes.netlify.app/). Ils sont liés depuis les leçons. L'application de quiz peut être exécutée localement ou déployée sur Azure ; suivez les instructions dans le dossier `quiz-app`. Ils sont progressivement localisés.
## Besoin d'aide
Vous avez des suggestions ou avez trouvé des erreurs d'orthographe ou de code ? Ouvrez une issue ou créez une pull request.
Vous avez des suggestions ou avez trouvé des erreurs de code ou d'orthographe ? Ouvrez une issue ou créez une pull request.
## Remerciements spéciaux
* **✍️ Auteur principal :** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Éditrice :** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Illustratrice des sketchnotes :** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Créatrice du quiz :** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🎨 Illustratrice de sketchnotes :** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Créatrice de quiz :** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Contributeurs principaux :** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Autres programmes
Notre équipe produit d'autres programmes ! Découvrez-les :
Notre équipe produit d'autres programmes ! Découvrez :
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
- [IA générative pour débutants](https://aka.ms/genai-beginners)
- [IA générative pour débutants .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [IA générative avec JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [IA générative avec Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [IA pour débutants](https://aka.ms/ai-beginners)
- [Science des données pour débutants](https://aka.ms/datascience-beginners)
- [Apprentissage automatique pour débutants](https://aka.ms/ml-beginners)
- [Cybersécurité pour débutants](https://github.com/microsoft/Security-101)
- [Développement web pour débutants](https://aka.ms/webdev-beginners)
- [IoT pour débutants](https://aka.ms/iot-beginners)
- [Développement XR pour débutants](https://github.com/microsoft/xr-development-for-beginners)
- [Maîtriser GitHub Copilot pour une utilisation agentique](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Maîtriser GitHub Copilot pour les développeurs C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choisissez votre propre aventure avec Copilot](https://github.com/microsoft/CopilotAdventures)
---
**Avertissement** :
Ce document a été traduit à l'aide du service de traduction automatique [Co-op Translator](https://github.com/Azure/co-op-translator). Bien que nous nous efforcions d'assurer l'exactitude, veuillez noter que les traductions automatisées peuvent contenir des erreurs ou des inexactitudes. Le document original dans sa langue d'origine doit être considéré comme la source faisant autorité. Pour des informations critiques, il est recommandé de recourir à une traduction humaine professionnelle. Nous déclinons toute responsabilité en cas de malentendus ou d'interprétations erronées résultant de l'utilisation de cette traduction.
Ce document a été traduit à l'aide du service de traduction automatique [Co-op Translator](https://github.com/Azure/co-op-translator). Bien que nous nous efforcions d'assurer l'exactitude, veuillez noter que les traductions automatisées peuvent contenir des erreurs ou des inexactitudes. Le document original dans sa langue d'origine doit être considéré comme la source faisant autorité. Pour des informations critiques, il est recommandé de faire appel à une traduction humaine professionnelle. Nous déclinons toute responsabilité en cas de malentendus ou d'interprétations erronées résultant de l'utilisation de cette traduction.

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# אינטליגנציה מלאכותית למתחילים - תוכנית לימודים
# בינה מלאכותית למתחילים - תוכנית לימודים
|![סקיצה מאת @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.he.png)|
|:---:|
| אינטליגנציה מלאכותית למתחילים - _סקיצה מאת [@girlie_mac](https://twitter.com/girlie_mac)_ |
|![איור מאת @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.he.png)|
|:---:|
| בינה מלאכותית למתחילים - _איור מאת [@girlie_mac](https://twitter.com/girlie_mac)_ |
גלו את עולם ה**אינטליגנציה המלאכותית** (AI) עם תוכנית לימודים בת 12 שבועות ו-24 שיעורים! התוכנית כוללת שיעורים מעשיים, חידונים ומעבדות. היא ידידותית למתחילים ומכסה כלים כמו TensorFlow ו-PyTorch, וכן עוסקת באתיקה בתחום ה-AI.
גלו את עולם ה**בינה המלאכותית** (AI) עם תוכנית לימודים בת 12 שבועות ו-24 שיעורים! התוכנית כוללת שיעורים מעשיים, חידונים ומעבדות. היא ידידותית למתחילים ומכסה כלים כמו TensorFlow ו-PyTorch, וגם עוסקת באתיקה בבינה מלאכותית.
### 🌐 תמיכה רב-לשונית
### 🌐 תמיכה בריבוי שפות
#### נתמך באמצעות GitHub Action (אוטומטי ותמיד מעודכן)
#### נתמך באמצעות GitHub Action (אוטומטי ומעודכן תמיד)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](./README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](./README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**אם תרצו להוסיף שפות נוספות, רשימת השפות הנתמכות נמצאת [כאן](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**אם תרצו להוסיף שפות נוספות, ניתן למצוא רשימה של שפות נתמכות [כאן](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## הצטרפו לקהילה
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## הצטרפו לקהילה
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## מה תלמדו
## מה תלמדו
**[מפת חשיבה של הקורס](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[מפת חשיבה של הקורס](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
בתוכנית הלימודים הזו תלמדו:
בתוכנית זו תלמדו:
* גישות שונות לאינטליגנציה מלאכותית, כולל הגישה הסמלית ה"ישנה והטובה" עם **ייצוג ידע** והסקה ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **רשתות נוירונים** ו**למידה עמוקה**, שהן בלב ה-AI המודרני. נמחיש את הרעיונות מאחורי נושאים חשובים אלו באמצעות קוד בשני מסגרות פופולריות - [TensorFlow](http://Tensorflow.org) ו-[PyTorch](http://pytorch.org).
* **ארכיטקטורות נוירונים** לעבודה עם תמונות וטקסט. נסקור מודלים עדכניים, אך ייתכן שלא נעסוק במודלים המתקדמים ביותר.
* גישות פחות פופולריות ל-AI, כמו **אלגוריתמים גנטיים** ו**מערכות מרובות סוכנים**.
* גישות שונות לבינה מלאכותית, כולל הגישה ה"ישנה והטובה" הסימבולית עם **ייצוג ידע** והסקת מסקנות ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **רשתות נוירונים** ו**למידה עמוקה**, שהן בלב הבינה המלאכותית המודרנית. נמחיש את הרעיונות מאחורי נושאים חשובים אלו באמצעות קוד בשני מסגרות פופולריות - [TensorFlow](http://Tensorflow.org) ו-[PyTorch](http://pytorch.org).
* **ארכיטקטורות נוירוניות** לעבודה עם תמונות וטקסט. נסקור מודלים עדכניים, אך ייתכן שלא נעסוק במודלים המתקדמים ביותר.
* גישות פחות נפוצות בבינה מלאכותית, כמו **אלגוריתמים גנטיים** ו**מערכות מרובות סוכנים**.
מה לא נכלל בתוכנית הלימודים הזו:
מה לא נכלל בתוכנית זו:
> [מצאו את כל המשאבים הנוספים לקורס הזה באוסף Microsoft Learn שלנו](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [מצאו את כל המשאבים הנוספים לקורס באוסף Microsoft Learn שלנו](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* מקרי שימוש עסקיים של **AI בעסקים**. שקלו לקחת את מסלול הלימוד [מבוא ל-AI למשתמשים עסקיים](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) ב-Microsoft Learn, או [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), שפותח בשיתוף עם [INSEAD](https://www.insead.edu/).
* **למידת מכונה קלאסית**, שמתוארת היטב בתוכנית הלימודים שלנו [Machine Learning for Beginners](http://github.com/Microsoft/ML-for-Beginners).
* יישומי AI מעשיים שנבנו באמצעות **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. לשם כך, אנו ממליצים להתחיל עם מודולים Microsoft Learn עבור [ראייה](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [עיבוד שפה טבעית](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI עם Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** ואחרים.
* מסגרות ענן ספציפיות ל-ML כמו [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), או [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). שקלו להשתמש במסלולי הלימוד [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) ו-[Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI שיחתי** ו**צ'אט בוטים**. ישנו מסלול לימוד נפרד [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), ואתם יכולים גם לעיין ב[פוסט הזה](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) לפרטים נוספים.
* **מתמטיקה עמוקה** מאחורי למידה עמוקה. לשם כך, אנו ממליצים על הספר [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) מאת Ian Goodfellow, Yoshua Bengio ו-Aaron Courville, שזמין גם אונליין ב-[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* מקרי שימוש עסקיים של **בינה מלאכותית בעסקים**. מומלץ לקחת את מסלול הלמידה [מבוא לבינה מלאכותית למשתמשים עסקיים](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) ב-Microsoft Learn, או את [בית הספר לעסקים של AI](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), שפותח בשיתוף עם [INSEAD](https://www.insead.edu/).
* **למידת מכונה קלאסית**, שמתוארת היטב בתוכנית הלימודים שלנו [למידת מכונה למתחילים](http://github.com/Microsoft/ML-for-Beginners).
* יישומי AI מעשיים שנבנו באמצעות **[שירותי קוגניציה](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. לשם כך, מומלץ להתחיל עם המודולים Microsoft Learn עבור [ראייה ממוחשבת](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [עיבוד שפה טבעית](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[בינה מלאכותית גנרטיבית עם Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** ואחרים.
* מסגרות ענן ספציפיות ל-ML, כמו [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), או [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). מומלץ להשתמש במסלולי הלמידה [בניית פתרונות למידת מכונה עם Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) ו-[בניית פתרונות למידת מכונה עם Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **בינה מלאכותית שיחתית** ו**צ'אטבוטים**. יש מסלול למידה נפרד [יצירת פתרונות בינה מלאכותית שיחתית](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), וניתן גם לעיין ב[פוסט בבלוג זה](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) לפרטים נוספים.
* **מתמטיקה מעמיקה** מאחורי למידה עמוקה. לשם כך, מומלץ הספר [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) מאת איאן גודפלו, יושוע בנג'יו וארון קורוויל, הזמין גם באינטרנט בכתובת [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
למבוא עדין לנושאי _AI בענן_, תוכלו לשקול לקחת את מסלול הלימוד [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
להיכרות עדינה עם נושאי _AI בענן_, מומלץ לקחת את מסלול הלמידה [התחלה עם בינה מלאכותית ב-Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# תוכן
# תוכן
| | קישור לשיעור | PyTorch/Keras/TensorFlow | מעבדה |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [הגדרת הקורס](./lessons/0-course-setup/setup.md) | [הגדרת סביבת הפיתוח שלכם](./lessons/0-course-setup/how-to-run.md) | |
| I | [**מבוא ל-AI**](./lessons/1-Intro/README.md) | | |
| 01 | [מבוא והיסטוריה של AI](./lessons/1-Intro/README.md) | - | - |
| II | **AI סמלי** |
| 02 | [ייצוג ידע ומערכות מומחה](./lessons/2-Symbolic/README.md) | [מערכות מומחה](./lessons/2-Symbolic/Animals.ipynb) / [אונטולוגיה](./lessons/2-Symbolic/FamilyOntology.ipynb) /[גרף מושגים](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**מבוא לרשתות נוירונים**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [פרספטורון](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [מחברת](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [מעבדה](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [פרספטורון רב-שכבתי ויצירת מסגרת משלנו](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [מחברת](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [מעבדה](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [מבוא למסגרות עבודה (PyTorch/TensorFlow) ואוברפיטינג](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [מעבדה](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| | קישור לשיעור | PyTorch/Keras/TensorFlow | מעבדה |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [הגדרת הקורס](./lessons/0-course-setup/setup.md) | [הגדרת סביבת הפיתוח שלך](./lessons/0-course-setup/how-to-run.md) | |
| I | [**מבוא לבינה מלאכותית**](./lessons/1-Intro/README.md) | | |
| 01 | [מבוא והיסטוריה של בינה מלאכותית](./lessons/1-Intro/README.md) | - | - |
| II | **בינה מלאכותית סימבולית** |
| 02 | [ייצוג ידע ומערכות מומחה](./lessons/2-Symbolic/README.md) | [מערכות מומחה](./lessons/2-Symbolic/Animals.ipynb) / [אונטולוגיה](./lessons/2-Symbolic/FamilyOntology.ipynb) /[גרף מושגים](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**מבוא לרשתות נוירונים**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [פרספטרון](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [מחברת](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [מעבדה](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [פרספטרון רב-שכבתי ויצירת מסגרת משלנו](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [מחברת](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [מעבדה](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [מבוא למסגרות (PyTorch/TensorFlow) ואוברפיטינג](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [מעבדה](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**ראייה ממוחשבת**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [חקור ראייה ממוחשבת ב-Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [מבוא לראייה ממוחשבת. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [מחברת](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [מעבדה](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [רשתות עצביות קונבולוציוניות](./lessons/4-ComputerVision/07-ConvNets/README.md) & [ארכיטקטורות CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [מעבדה](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
@ -86,15 +86,15 @@ CO_OP_TRANSLATOR_METADATA:
| 11 | [זיהוי אובייקטים](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [מעבדה](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [סגמנטציה סמנטית. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**עיבוד שפה טבעית**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [חקור עיבוד שפה טבעית ב-Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [ייצוג טקסט. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [הטמעות מילים סמנטיות. Word2Vec ו-GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [מודלים לשוניים. אימון הטמעות משלך](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [מעבדה](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [רשתות עצביות חוזרות](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [רשתות חוזרות גנרטיביות](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [מעבדה](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [טרנספורמרים. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [זיהוי ישויות בשם](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [מעבדה](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [מודלים לשוניים גדולים, תכנות פרומפט ומשימות Few-Shot](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **טכניקות AI נוספות** || |
| 13 | [ייצוג טקסט. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [הטמעות סמנטיות של מילים. Word2Vec ו-GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [מודלים של שפה. אימון הטמעות משלך](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [מעבדה](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [רשתות עצביות חוזרות](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [רשתות חוזרות גנרטיביות](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [מעבדה](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [טרנספורמרים. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [זיהוי ישויות בשם](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [מעבדה](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [מודלים של שפה גדולה, תכנות פרומפט ומשימות Few-Shot](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **טכניקות AI אחרות** || |
| 21 | [אלגוריתמים גנטיים](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [מחברת](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [למידת חיזוק עמוקה](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [מעבדה](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [מערכות מרובות סוכנים](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
@ -103,49 +103,49 @@ CO_OP_TRANSLATOR_METADATA:
| IX | **תוספות** | | |
| 25 | [רשתות מולטי-מודל, CLIP ו-VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [מחברת](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## כל שיעור מכיל
## כל שיעור כולל
* חומר קריאה מקדים
* מחברות Jupyter ניתנות להרצה, שלרוב מותאמות למסגרת העבודה (**PyTorch** או **TensorFlow**). המחברות מכילות גם הרבה חומר תיאורטי, ולכן כדי להבין את הנושא יש לעבור לפחות על גרסה אחת של המחברת (PyTorch או TensorFlow).
* **מעבדות** זמינות עבור חלק מהנושאים, ומאפשרות לך ליישם את החומר הנלמד על בעיה מסוימת.
* חלק מהסעיפים מכילים קישורים למודולים של [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) שמכסים נושאים קשורים.
* חומר קריאה מקדים
* מחברות Jupyter ניתנות להרצה, שלרוב מותאמות למסגרת (**PyTorch** או **TensorFlow**). המחברת כוללת גם הרבה חומר תיאורטי, ולכן כדי להבין את הנושא יש לעבור לפחות על גרסה אחת של המחברת (PyTorch או TensorFlow).
* **מעבדות** זמינות עבור חלק מהנושאים, שמאפשרות לך ליישם את החומר שלמדת על בעיה ספציפית.
* חלק מהסעיפים כוללים קישורים למודולים של [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) שמכסים נושאים קשורים.
## התחלת העבודה
## איך מתחילים
- יצרנו [שיעור הגדרה](./lessons/0-course-setup/setup.md) שיעזור לך להגדיר את סביבת הפיתוח שלך. - למורים, יצרנו גם [שיעור הגדרה לתוכנית הלימודים](./lessons/0-course-setup/for-teachers.md)!
- כיצד [להריץ את הקוד ב-VSCode או Codepace](./lessons/0-course-setup/how-to-run.md)
- יצרנו [שיעור הגדרות](./lessons/0-course-setup/setup.md) שיעזור לך להגדיר את סביבת הפיתוח שלך.
- עבור מחנכים, יצרנו גם [שיעור הגדרות תוכנית לימודים](./lessons/0-course-setup/for-teachers.md)!
- איך [להריץ את הקוד ב-VSCode או Codepace](./lessons/0-course-setup/how-to-run.md)
בצעו את השלבים הבאים:
בצע את השלבים הבאים:
פיצול המאגר: לחצו על כפתור "Fork" בפינה הימנית העליונה של העמוד.
1. בצע Fork למאגר: לחץ על כפתור "Fork" בפינה הימנית העליונה של העמוד.
2. שיבוט המאגר: `git clone https://github.com/microsoft/AI-For-Beginners.git`
שכפול המאגר: `git clone https://github.com/microsoft/AI-For-Beginners.git`
אל תשכח לככב (🌟) את המאגר כדי למצוא אותו בקלות מאוחר יותר.
אל תשכחו לככב (🌟) במאגר כדי למצוא אותו בקלות מאוחר יותר.
## פגוש לומדים אחרים
## הכירו לומדים נוספים
הצטרף ל-[שרת הדיסקורד הרשמי של AI](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) כדי לפגוש ולהתחבר עם לומדים אחרים שלוקחים את הקורס ולקבל תמיכה.
הצטרפו ל-[שרת ה-Discord הרשמי של AI](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) כדי להכיר ולהתחבר עם לומדים נוספים שלוקחים את הקורס ולקבל תמיכה.
אם יש לכם משוב על המוצר או שאלות במהלך הבנייה, בקרו ב-[פורום המפתחים של Azure AI Foundry](https://aka.ms/foundry/forum)
אם יש לך משוב על מוצרים או שאלות בזמן הבנייה, בקר ב-[פורום המפתחים של Azure AI Foundry](https://aka.ms/foundry/forum).
## חידונים
> **הערה לגבי חידונים**: כל החידונים נמצאים בתיקיית Quiz-app ב-etc\quiz-app, או [באופן מקוון כאן](https://ff-quizzes.netlify.app/). הם מקושרים מתוך השיעורים. ניתן להפעיל את אפליקציית החידונים באופן מקומי או לפרוס אותה ב-Azure; עקבו אחר ההוראות בתיקיית `quiz-app`. הם מתורגמים בהדרגה.
## דרושים עזרה
> **הערה לגבי חידונים**: כל החידונים נמצאים בתיקיית Quiz-app בנתיב etc\quiz-app, או [באופן מקוון כאן](https://ff-quizzes.netlify.app/). הם מקושרים מתוך השיעורים. ניתן להפעיל את אפליקציית החידונים באופן מקומי או לפרוס אותה ב-Azure; עקבו אחר ההוראות בתיקיית `quiz-app`. הם מתורגמים בהדרגה.
## דרוש עזרה
יש לכם הצעות או שמצאתם שגיאות כתיב או קוד? פתחו issue או צרו pull request.
יש לכם הצעות או מצאתם שגיאות כתיב או קוד? פתחו בעיה או צרו בקשת משיכה.
## תודה מיוחדת
* **✍️ מחבר ראשי:** [דמיטרי סושניקוב](http://soshnikov.com), דוקטור
* **🔥 עורך:** [ג'ן לופר](https://twitter.com/jenlooper), דוקטור
* **🎨 מאיירת סקצ'נוטים:** [טומומי אימורה](https://twitter.com/girlie_mac)
* **✅ יוצרת חידונים:** [לטיפה בלו](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 תורמים מרכזיים:** [יבגני פישצ'יק](https://github.com/Pe4enIks)
* **✍️ מחבר ראשי:** [Dmitry Soshnikov](http://soshnikov.com), דוקטור
* **🔥 עורך:** [Jen Looper](https://twitter.com/jenlooper), דוקטור
* **🎨 מאייר סקצ'נוט:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ יוצר שאלונים:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 תורמים מרכזיים:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## תכניות לימוד נוספות
הצוות שלנו יוצר תכניות לימוד נוספות! בדקו את:
הצוות שלנו מייצר תכניות לימוד נוספות! בדקו:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
@ -165,4 +165,4 @@ CO_OP_TRANSLATOR_METADATA:
---
**כתב ויתור**:
מסמך זה תורגם באמצעות שירות תרגום מבוסס בינה מלאכותית [Co-op Translator](https://github.com/Azure/co-op-translator). למרות שאנו שואפים לדיוק, יש לקחת בחשבון שתרגומים אוטומטיים עשויים להכיל שגיאות או אי-דיוקים. המסמך המקורי בשפתו המקורית נחשב למקור הסמכותי. למידע קריטי, מומלץ להשתמש בתרגום מקצועי על ידי מתרגם אנושי. איננו נושאים באחריות לכל אי-הבנה או פרשנות שגויה הנובעת משימוש בתרגום זה.
מסמך זה תורגם באמצעות שירות תרגום מבוסס בינה מלאכותית [Co-op Translator](https://github.com/Azure/co-op-translator). למרות שאנו שואפים לדיוק, יש לקחת בחשבון שתרגומים אוטומטיים עשויים להכיל שגיאות או אי-דיוקים. המסמך המקורי בשפתו המקורית נחשב למקור הסמכותי. למידע קריטי, מומלץ להשתמש בתרגום מקצועי על ידי בני אדם. איננו נושאים באחריות לכל אי-הבנה או פרשנות שגויה הנובעת משימוש בתרגום זה.

112
translations/hi/README.md
View File

@ -1,8 +1,8 @@
<!--
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@ -21,21 +21,21 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# शुरुआती लोगों के लिए कृत्रिम बुद्धिमत्ता - एक पाठ्यक्रम
# शुरुआती लोगों के लिए कृत्रिम बुद्धिमत्ता - एक पाठ्यक्रम
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.hi.png)|
|:---:|
| शुरुआती लोगों के लिए AI - _[@girlie_mac](https://twitter.com/girlie_mac) द्वारा स्केच_ |
| शुरुआती लोगों के लिए AI - _[@girlie_mac](https://twitter.com/girlie_mac) द्वारा स्केच नोट_ |
**कृत्रिम बुद्धिमत्ता** (AI) की दुनिया को हमारे 12-सप्ताह, 24-पाठ वाले पाठ्यक्रम के साथ खोजें! इसमें व्यावहारिक पाठ, क्विज़ और प्रयोगशालाएं शामिल हैं। यह पाठ्यक्रम शुरुआती लोगों के लिए अनुकूल है और इसमें TensorFlow और PyTorch जैसे उपकरणों के साथ-साथ AI में नैतिकता भी शामिल है।
**कृत्रिम बुद्धिमत्ता** (AI) की दुनिया का अन्वेषण करें हमारे 12-सप्ताह, 24-पाठ वाले पाठ्यक्रम के साथ! इसमें व्यावहारिक पाठ, क्विज़ और लैब्स शामिल हैं। यह पाठ्यक्रम शुरुआती लोगों के लिए अनुकूल है और इसमें TensorFlow और PyTorch जैसे टूल्स के साथ-साथ AI में नैतिकता को भी शामिल किया गया है।
### 🌐 बहुभाषी समर्थन
### 🌐 बहुभाषी समर्थन
#### GitHub Action के माध्यम से समर्थित (स्वचालित और हमेशा अद्यतन)
#### GitHub Action के माध्यम से समर्थित (स्वचालित और हमेशा अद्यतन)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](./README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**यदि आप अतिरिक्त अनुवाद चाहते हैं, तो समर्थित भाषाओं की सूची [यहां](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) उपलब्ध है।**
**यदि आप अतिरिक्त भाषाओं में अनुवाद चाहते हैं, तो समर्थित भाषाओं की सूची [यहां](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) देखें।**
## समुदाय से जुड़ें
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -47,76 +47,76 @@ CO_OP_TRANSLATOR_METADATA:
इस पाठ्यक्रम में, आप सीखेंगे:
* कृत्रिम बुद्धिमत्ता के विभिन्न दृष्टिकोण, जिसमें "पुराने" प्रतीकात्मक दृष्टिकोण शामिल हैं, जैसे **ज्ञान प्रतिनिधित्व** और तर्क ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))।
* **न्यूरल नेटवर्क** और **डीप लर्निंग**, जो आधुनिक AI के केंद्र में हैं। हम इन महत्वपूर्ण विषयों के पीछे के विचारों को [TensorFlow](http://Tensorflow.org) और [PyTorch](http://pytorch.org) जैसे लोकप्रिय फ्रेमवर्क्स के कोड के माध्यम से समझाएंगे।
* छवियों और पाठ के साथ काम करने के लिए **न्यूरल आर्किटेक्चर**। हम हाल के मॉडलों को कवर करेंगे लेकिन अत्याधुनिक तकनीकों में थोड़ी कमी हो सकती है।
* **न्यूरल नेटवर्क्स** और **डीप लर्निंग**, जो आधुनिक AI के केंद्र में हैं। हम इन महत्वपूर्ण विषयों के पीछे की अवधारणाओं को दो लोकप्रिय फ्रेमवर्क - [TensorFlow](http://Tensorflow.org) और [PyTorch](http://pytorch.org) - में कोड का उपयोग करके समझाएंगे।
* छवियों और पाठ के साथ काम करने के लिए **न्यूरल आर्किटेक्चर**। हम हाल के मॉडलों को कवर करेंगे, लेकिन अत्याधुनिक तकनीकों में थोड़े पीछे हो सकते हैं।
* कम लोकप्रिय AI दृष्टिकोण, जैसे **जेनेटिक एल्गोरिदम** और **मल्टी-एजेंट सिस्टम्स**।
इस पाठ्यक्रम में हम क्या कवर नहीं करेंगे:
> [इस पाठ्यक्रम के लिए सभी अतिरिक्त संसाधन हमारे Microsoft Learn संग्रह में खोजें](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [इस पाठ्यक्रम के लिए सभी अतिरिक्त संसाधन हमारी Microsoft Learn संग्रह में पाएं](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **व्यवसाय में AI** का उपयोग करने के व्यावसायिक मामले। इसके लिए, [व्यवसाय उपयोगकर्ताओं के लिए AI का परिचय](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) या [AI बिजनेस स्कूल](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) पर विचार करें।
* **व्यवसाय में AI** का उपयोग करने के व्यावसायिक मामले। इसके लिए, [व्यवसाय उपयोगकर्ताओं के लिए AI का परिचय](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) या [AI बिजनेस स्कूल](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) लेने पर विचार करें, जिसे [INSEAD](https://www.insead.edu/) के सहयोग से विकसित किया गया है।
* **क्लासिक मशीन लर्निंग**, जिसे हमारे [शुरुआती लोगों के लिए मशीन लर्निंग पाठ्यक्रम](http://github.com/Microsoft/ML-for-Beginners) में अच्छी तरह से वर्णित किया गया है।
* **[कॉग्निटिव सर्विसेज](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** का उपयोग करके व्यावहारिक AI अनुप्रयोग। इसके लिए, [Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum) जैसे मॉड्यूल से शुरुआत करें।
* **क्लाउड फ्रेमवर्क्स**, जैसे [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)।
* **संवादी AI** और **चैट बॉट्स**। इसके लिए [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) पर विचार करें।
* **डीप लर्निंग के पीछे गहन गणित**। इसके लिए, [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) पुस्तक की सिफारिश की जाती है।
* **[कॉग्निटिव सर्विसेज](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** का उपयोग करके व्यावहारिक AI अनुप्रयोग। इसके लिए, हम Microsoft Learn के [विज़न](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [नेचुरल लैंग्वेज प्रोसेसिंग](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI सेवा के साथ जनरेटिव AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** और अन्य मॉड्यूल से शुरुआत करने की सिफारिश करते हैं।
* **विशिष्ट ML क्लाउड फ्रेमवर्क**, जैसे [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), या [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)। [Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) और [Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) के साथ मशीन लर्निंग समाधान बनाने और संचालित करने के लिए सीखने के रास्तों का उपयोग करने पर विचार करें।
* **संवादी AI** और **चैट बॉट्स**। इसके लिए, [संवादी AI समाधान बनाएं](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) सीखने का रास्ता लें, और अधिक विवरण के लिए [इस ब्लॉग पोस्ट](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) को देखें।
* **डीप लर्निंग के पीछे की गहरी गणितीय अवधारणाएं**। इसके लिए, हम [डीप लर्निंग](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) पुस्तक की सिफारिश करते हैं, जिसे Ian Goodfellow, Yoshua Bengio और Aaron Courville द्वारा लिखा गया है, और यह ऑनलाइन [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) पर भी उपलब्ध है।
क्लाउड में _AI_ के लिए एक सरल परिचय के लिए, [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) पर विचार करें।
_क्लाउड में AI_ विषयों का एक सरल परिचय पाने के लिए, आप [Azure पर कृत्रिम बुद्धिमत्ता के साथ शुरुआत करें](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) सीखने का रास्ता ले सकते हैं।
# सामग्री
| | पाठ लिंक | PyTorch/Keras/TensorFlow | प्रयोगशाला |
| | पाठ लिंक | PyTorch/Keras/TensorFlow | लैब |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [पाठ्यक्रम सेटअप](./lessons/0-course-setup/setup.md) | [अपना विकास वातावरण सेट करें](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI का परिचय**](./lessons/1-Intro/README.md) | | |
| 01 | [AI का परिचय और इतिहास](./lessons/1-Intro/README.md) | - | - |
| II | **प्रतीकात्मक AI** |
| 02 | [ज्ञान प्रतिनिधित्व और विशेषज्ञ प्रणाली](./lessons/2-Symbolic/README.md) | [विशेषज्ञ प्रणाली](./lessons/2-Symbolic/Animals.ipynb) / [ऑन्टोलॉजी](./lessons/2-Symbolic/FamilyOntology.ipynb) /[कॉन्सेप्ट ग्राफ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**न्यूरल नेटवर्क का परिचय**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [परसेप्ट्रॉन](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [नोटबुक](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [प्रयोगशाला](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [मल्टी-लेयर्ड परसेप्ट्रॉन और अपना फ्रेमवर्क बनाना](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [नोटबुक](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [प्रयोगशाला](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| III | [**न्यूरल नेटवर्क्स का परिचय**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [परसेप्ट्रॉन](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [नोटबुक](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [लैब](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [मल्टी-लेयर्ड परसेप्ट्रॉन और अपना फ्रेमवर्क बनाना](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [नोटबुक](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [लैब](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [फ्रेमवर्क्स (PyTorch/TensorFlow) और ओवरफिटिंग का परिचय](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [प्रयोगशाला](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**कंप्यूटर विज़न**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure पर कंप्यूटर विज़न का अन्वेषण करें](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [कंप्यूटर विज़न का परिचय। OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [नोटबुक](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [प्रयोगशाला](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [कन्वोल्यूशनल न्यूरल नेटवर्क्स](./lessons/4-ComputerVision/07-ConvNets/README.md) और [CNN आर्किटेक्चर](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [प्रयोगशाला](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [प्री-ट्रेंड नेटवर्क्स और ट्रांसफर लर्निंग](./lessons/4-ComputerVision/08-TransferLearning/README.md) और [ट्रेनिंग ट्रिक्स](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [प्रयोगशाला](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [ऑटोएन्कोडर्स और VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [जेनरेटिव एडवर्सेरियल नेटवर्क्स और आर्टिस्टिक स्टाइल ट्रांसफर](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 10 | [जनरेटिव एडवर्सेरियल नेटवर्क्स और आर्टिस्टिक स्टाइल ट्रांसफर](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [ऑब्जेक्ट डिटेक्शन](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [प्रयोगशाला](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [सेमांटिक सेगमेंटेशन। U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**नेचुरल लैंग्वेज प्रोसेसिंग**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure पर नेचुरल लैंग्वेज प्रोसेसिंग का अन्वेषण करें](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [टेक्स्ट रिप्रेजेंटेशन। Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [सेमांटिक वर्ड एम्बेडिंग्स। Word2Vec और GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [लैंग्वेज मॉडलिंग। अपने एम्बेडिंग्स को ट्रेन करें](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [प्रयोगशाला](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [रिकरेंट न्यूरल नेटवर्क्स](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [जेनरेटिव रिकारेंट नेटवर्क्स](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [प्रयोगशाला](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ट्रांसफॉर्मर्स। BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [नेम्ड एंटिटी रिकग्निशन](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [प्रयोगशाला](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [लार्ज लैंग्वेज मॉडल्स, प्रॉम्प्ट प्रोग्रामिंग और फ्यू-शॉट टास्क्स](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [टेक्स्ट रिप्रेजेंटेशन। Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [सेमांटिक वर्ड एम्बेडिंग्स। Word2Vec और GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [लैंग्वेज मॉडलिंग। अपने एम्बेडिंग्स को ट्रेन करें](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [प्रयोगशाला](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [रिकरेंट न्यूरल नेटवर्क्स](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [जनरेटिव रिक्रेंट नेटवर्क्स](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [प्रयोगशाला](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ट्रांसफॉर्मर्स। BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [नेम्ड एंटिटी रिकग्निशन](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [प्रयोगशाला](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [बड़े लैंग्वेज मॉडल्स, प्रॉम्प्ट प्रोग्रामिंग और फ्यू-शॉट टास्क्स](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **अन्य AI तकनीकें** || |
| 21 | [जेनेटिक एल्गोरिदम](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [नोटबुक](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [डीप रिइंफोर्समेंट लर्निंग](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [प्रयोगशाला](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [मल्टी-एजेंट सिस्टम्स](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI नैतिकता** | | |
| 24 | [AI नैतिकता और जिम्मेदार AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: जिम्मेदार AI सिद्धांत](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **अतिरिक्त** | | |
| IX | **अतिरिक्त सामग्री** | | |
| 25 | [मल्टी-मोडल नेटवर्क्स, CLIP और VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [नोटबुक](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## प्रत्येक पाठ में शामिल है
* पूर्व-पढ़ाई सामग्री
* निष्पादन योग्य Jupyter नोटबुक्स, जो अक्सर फ्रेमवर्क (**PyTorch** या **TensorFlow**) के लिए विशिष्ट होती हैं। निष्पादन योग्य नोटबुक में बहुत सारा सैद्धांतिक सामग्री भी होती है, इसलिए विषय को समझने के लिए आपको कम से कम एक संस्करण (PyTorch या TensorFlow) को पढ़ना होगा।
* **प्रयोगशालाएं**, जो कुछ विषयों के लिए उपलब्ध हैं, आपको सीखी गई सामग्री को किसी विशिष्ट समस्या पर लागू करने का अवसर देती हैं।
* निष्पादनीय Jupyter नोटबुक्स, जो अक्सर फ्रेमवर्क (**PyTorch** या **TensorFlow**) के लिए विशिष्ट होती हैं। निष्पादनीय नोटबुक में बहुत सारा सैद्धांतिक सामग्री भी होती है, इसलिए विषय को समझने के लिए आपको कम से कम एक संस्करण (PyTorch या TensorFlow) को पढ़ना होगा।
* **प्रयोगशालाएं**, जो कुछ विषयों के लिए उपलब्ध हैं, आपको सीखी गई सामग्री को किसी विशेष समस्या पर लागू करने का अवसर देती हैं।
* कुछ अनुभागों में [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) मॉड्यूल्स के लिंक शामिल हैं, जो संबंधित विषयों को कवर करते हैं।
## शुरुआत करें
- हमने आपके विकास पर्यावरण को सेटअप करने में मदद के लिए एक [सेटअप पाठ](./lessons/0-course-setup/setup.md) बनाया है।
- शिक्षकों के लिए, हमने आपके लिए एक [पाठ्यक्रम सेटअप पाठ](./lessons/0-course-setup/for-teachers.md) भी बनाया है!
- शिक्षकों के लिए, हमने एक [पाठ्यक्रम सेटअप पाठ](./lessons/0-course-setup/for-teachers.md) भी बनाया है!
- [VSCode या Codepace में कोड कैसे चलाएं](./lessons/0-course-setup/how-to-run.md)
इन चरणों का पालन करें:
इन चरणों का पालन करें:
रिपॉजिटरी को फोर्क करें: इस पेज के ऊपर-दाईं ओर "Fork" बटन पर क्लिक करें।
@ -126,44 +126,44 @@ CO_OP_TRANSLATOR_METADATA:
## अन्य शिक्षार्थियों से मिलें
हमारे [आधिकारिक AI Discord सर्वर](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) से जुड़ें, इस कोर्स को लेने वाले अन्य शिक्षार्थियों से मिलने और नेटवर्क बनाने के लिए और सहायता प्राप्त करने के लिए।
हमारे [आधिकारिक AI Discord सर्वर](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) से जुड़ें, इस पाठ्यक्रम को लेने वाले अन्य शिक्षार्थियों से मिलने और नेटवर्क बनाने के लिए और सहायता प्राप्त करने के लिए।
यदि आपके पास उत्पाद प्रतिक्रिया या प्रश्न हैं, तो हमारे [Azure AI Foundry डेवलपर फोरम](https://aka.ms/foundry/forum) पर जाएं।
## क्विज़
> **क्विज़ के बारे में एक नोट**: सभी क्विज़ Quiz-app फ़ोल्डर में etc\quiz-app में संग्रहीत हैं, या [ऑनलाइन यहां](https://ff-quizzes.netlify.app/) उपलब्ध हैं। इन्हें पाठों के भीतर से जोड़ा गया है। क्विज़ ऐप को स्थानीय रूप से चलाया जा सकता है या Azure पर डिप्लॉय किया जा सकता है; `quiz-app` फ़ोल्डर में दिए गए निर्देशों का पालन करें। इन्हें धीरे-धीरे स्थानीय भाषाओं में अनुवादित किया जा रहा है।
> **क्विज़ के बारे में एक नोट**: सभी क्विज़ Quiz-app फ़ोल्डर में etc\quiz-app में संग्रहीत हैं, या [ऑनलाइन यहां](https://ff-quizzes.netlify.app/) उपलब्ध हैं। इन्हें पाठों के भीतर से जोड़ा गया है। क्विज़ ऐप को स्थानीय रूप से चलाया जा सकता है या Azure पर डिप्लॉय किया जा सकता है; `quiz-app` फ़ोल्डर में दिए गए निर्देशों का पालन करें। इन्हें धीरे-धीरे स्थानीयकृत किया जा रहा है।
## मदद चाहिए
क्या आपके पास सुझाव हैं या आपने वर्तनी या कोड में त्रुटियां पाई हैं? एक मुद्दा उठाएं या एक पुल अनुरोध बनाएं।
## विशेष धन्यवाद
* **✍️ मुख्य लेखक:** [Dmitry Soshnikov](http://soshnikov.com), पीएचडी
* **🔥 संपादक:** [Jen Looper](https://twitter.com/jenlooper), पीएचडी
* **✍️ मुख्य लेखक:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 संपादक:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 स्केच नोट इलस्ट्रेटर:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ क्विज़ निर्माता:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **✅ क्विज निर्माता:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 मुख्य योगदानकर्ता:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## अन्य पाठ्यक्रम
हमारी टीम अन्य पाठ्यक्रम भी बनाती है! इन्हें देखें:
- [शुरुआती के लिए जनरेटिव एआई](https://aka.ms/genai-beginners)
- [शुरुआती के लिए जनरेटिव एआई .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [जावास्क्रिप्ट के साथ जनरेटिव एआई](https://github.com/microsoft/generative-ai-with-javascript)
- [जावा के साथ जनरेटिव एआई](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [शुरुआती के लिए एआई](https://aka.ms/ai-beginners)
- [शुरुआती के लिए डेटा साइंस](https://aka.ms/datascience-beginners)
- [शुरुआती के लिए मशीन लर्निंग](https://aka.ms/ml-beginners)
- [शुरुआती के लिए साइबर सुरक्षा](https://github.com/microsoft/Security-101)
- [शुरुआती के लिए वेब विकास](https://aka.ms/webdev-beginners)
- [शुरुआती के लिए IoT](https://aka.ms/iot-beginners)
- [शुरुआती के लिए XR विकास](https://github.com/microsoft/xr-development-for-beginners)
- [एजेंटिक उपयोग के लिए GitHub Copilot में महारत हासिल करना](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [C#/.NET डेवलपर्स के लिए GitHub Copilot में महारत हासिल करना](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [अपना खुद का Copilot एडवेंचर चुनें](https://github.com/microsoft/CopilotAdventures)
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---
**अस्वीकरण**:
यह दस्तावेज़ AI अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) का उपयोग करके अनुवादित किया गया है। जबकि हम सटीकता के लिए प्रयासरत हैं, कृपया ध्यान दें कि स्वचालित अनुवाद में त्रुटियां या अशुद्धियां हो सकती हैं। मूल भाषा में उपलब्ध मूल दस्तावेज़ को प्रामाणिक स्रोत माना जाना चाहिए। महत्वपूर्ण जानकारी के लिए, पेशेवर मानव अनुवाद की सिफारिश की जाती है। इस अनुवाद के उपयोग से उत्पन्न किसी भी गलतफहमी या गलत व्याख्या के लिए हम उत्तरदायी नहीं हैं।
यह दस्तावेज़ AI अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) का उपयोग करके अनुवादित किया गया है। जबकि हम सटीकता के लिए प्रयास करते हैं, कृपया ध्यान दें कि स्वचालित अनुवादों में त्रुटियां या अशुद्धियां हो सकती हैं। मूल भाषा में उपलब्ध मूल दस्तावेज़ को आधिकारिक स्रोत माना जाना चाहिए। महत्वपूर्ण जानकारी के लिए, पेशेवर मानव अनुवाद की सिफारिश की जाती है। इस अनुवाद के उपयोग से उत्पन्न किसी भी गलतफहमी या गलत व्याख्या के लिए हम उत्तरदायी नहीं हैं।

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@ -1,8 +1,8 @@
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@ -21,19 +21,19 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# 人工智能初學者課程 - 課程大綱
# 人工智能入門課程 - 課程大綱
|![由 @girlie_mac 繪製的速寫筆記 https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.hk.png)|
|:---:|
| 人工智能初學者課程 - _速寫筆記由 [@girlie_mac](https://twitter.com/girlie_mac) 繪製_ |
| 人工智能入門課程 - _由 [@girlie_mac](https://twitter.com/girlie_mac) 繪製的手繪筆記_ |
探索 **人工智能** (AI) 的世界，通過我們為期 12 週、共 24 節課的課程！課程包括實用教學、測驗和實驗室練習。這是一個適合初學者的課程，涵蓋了如 TensorFlow 和 PyTorch 等工具，以及 AI 的倫理問題。
探索 **人工智能** (AI) 的世界，透過我們為期 12 週、共 24 節課的課程！課程包括實用的教學內容、測驗和實驗室練習。這是一個適合初學者的課程，涵蓋了 TensorFlow 和 PyTorch 等工具，以及人工智能的倫理問題。
### 🌐 多語言支持
#### 通過 GitHub Action 支持（自動化且始終保持最新）
#### 透過 GitHub Action 支持（自動化且始終保持最新）
[法文](../fr/README.md) | [西班牙文](../es/README.md) | [德文](../de/README.md) | [俄文](../ru/README.md) | [阿拉伯文](../ar/README.md) | [波斯文 (法爾西)](../fa/README.md) | [烏爾都文](../ur/README.md) | [中文 (簡體)](../zh/README.md) | [中文 (繁體，澳門)](../mo/README.md) | [中文 (繁體，香港)](./README.md) | [中文 (繁體，台灣)](../tw/README.md) | [日文](../ja/README.md) | [韓文](../ko/README.md) | [印地文](../hi/README.md) | [孟加拉文](../bn/README.md) | [馬拉地文](../mr/README.md) | [尼泊爾文](../ne/README.md) | [旁遮普文 (古木基)](../pa/README.md) | [葡萄牙文 (葡萄牙)](../pt/README.md) | [葡萄牙文 (巴西)](../br/README.md) | [意大利文](../it/README.md) | [波蘭文](../pl/README.md) | [土耳其文](../tr/README.md) | [希臘文](../el/README.md) | [泰文](../th/README.md) | [瑞典文](../sv/README.md) | [丹麥文](../da/README.md) | [挪威文](../no/README.md) | [芬蘭文](../fi/README.md) | [荷蘭文](../nl/README.md) | [希伯來文](../he/README.md) | [越南文](../vi/README.md) | [印尼文](../id/README.md) | [馬來文](../ms/README.md) | [他加祿文 (菲律賓)](../tl/README.md) | [斯瓦希里文](../sw/README.md) | [匈牙利文](../hu/README.md) | [捷克文](../cs/README.md) | [斯洛伐克文](../sk/README.md) | [羅馬尼亞文](../ro/README.md) | [保加利亞文](../bg/README.md) | [塞爾維亞文 (西里爾字母)](../sr/README.md) | [克羅地亞文](../hr/README.md) | [斯洛文尼亞文](../sl/README.md) | [烏克蘭文](../uk/README.md) | [緬甸文 (緬甸)](../my/README.md)
[法文](../fr/README.md) | [西班牙文](../es/README.md) | [德文](../de/README.md) | [俄文](../ru/README.md) | [阿拉伯文](../ar/README.md) | [波斯文 (法爾西)](../fa/README.md) | [烏爾都文](../ur/README.md) | [中文 (簡體)](../zh/README.md) | [中文 (繁體，澳門)](../mo/README.md) | [中文 (繁體，香港)](./README.md) | [中文 (繁體，台灣)](../tw/README.md) | [日文](../ja/README.md) | [韓文](../ko/README.md) | [印地文](../hi/README.md) | [孟加拉文](../bn/README.md) | [馬拉地文](../mr/README.md) | [尼泊爾文](../ne/README.md) | [旁遮普文 (古木基文)](../pa/README.md) | [葡萄牙文 (葡萄牙)](../pt/README.md) | [葡萄牙文 (巴西)](../br/README.md) | [意大利文](../it/README.md) | [波蘭文](../pl/README.md) | [土耳其文](../tr/README.md) | [希臘文](../el/README.md) | [泰文](../th/README.md) | [瑞典文](../sv/README.md) | [丹麥文](../da/README.md) | [挪威文](../no/README.md) | [芬蘭文](../fi/README.md) | [荷蘭文](../nl/README.md) | [希伯來文](../he/README.md) | [越南文](../vi/README.md) | [印尼文](../id/README.md) | [馬來文](../ms/README.md) | [他加祿文 (菲律賓文)](../tl/README.md) | [斯瓦希里文](../sw/README.md) | [匈牙利文](../hu/README.md) | [捷克文](../cs/README.md) | [斯洛伐克文](../sk/README.md) | [羅馬尼亞文](../ro/README.md) | [保加利亞文](../bg/README.md) | [塞爾維亞文 (西里爾文)](../sr/README.md) | [克羅地亞文](../hr/README.md) | [斯洛文尼亞文](../sl/README.md) | [烏克蘭文](../uk/README.md) | [緬甸文 (緬甸)](../my/README.md)
**如果您希望支持其他翻譯語言，請參考 [此處](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
@ -46,122 +46,123 @@ CO_OP_TRANSLATOR_METADATA:
在這個課程中，您將學到：
* 不同的人工智能方法，包括使用 **知識表示** 和推理的「經典」符號方法 ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))。
* **神經網絡** 和 **深度學習**，這是現代 AI 的核心。我們將使用兩個最受歡迎的框架 [TensorFlow](http://Tensorflow.org) 和 [PyTorch](http://pytorch.org) 的代碼來說明這些重要主題背後的概念。
* 用於處理圖像和文本的 **神經架構**。我們將涵蓋一些近期的模型，但可能不包括最前沿的技術。
* 不太流行的 AI 方法，例如 **遺傳算法** 和 **多代理系統**。
* 不同的人工智能方法，包括傳統的符號方法，例如 **知識表示** 和推理 ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))。
* **神經網絡** 和 **深度學習**，這些是現代人工智能的核心。我們將使用兩個最受歡迎的框架 [TensorFlow](http://Tensorflow.org) 和 [PyTorch](http://pytorch.org) 的程式碼來說明這些重要主題背後的概念。
* 用於處理影像和文本的 **神經架構**。我們將涵蓋最近的模型，但可能不包括最新的技術。
* 不太流行的人工智能方法，例如 **遺傳算法** 和 **多代理系統**。
本課程不會涵蓋：
我們不會在這個課程中涵蓋：
> [在 Microsoft Learn 集合中找到本課程的所有額外資源](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **AI 在商業中的應用案例**。建議參加 [商業用戶的 AI 入門](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，或 [AI 商業學院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)，該課程與 [INSEAD](https://www.insead.edu/) 合作開發。
* **經典機器學習**，這在我們的 [機器學習初學者課程](http://github.com/Microsoft/ML-for-Beginners) 中有詳細描述。
* 使用 **[認知服務](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** 構建的實際 AI 應用。建議從 Microsoft Learn 的模組開始學習 [視覺](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然語言處理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[Azure OpenAI Service 的生成式 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 等內容。
* 特定的 ML **雲框架**，如 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) 或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。建議參考 [使用 Azure Machine Learning 構建和運營機器學習解決方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 和 [使用 Azure Databricks 構建和運營機器學習解決方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
* **對話式 AI** 和 **聊天機器人**。有一個單獨的 [創建對話式 AI 解決方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，您也可以參考 [這篇博客文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) 獲取更多細節。
* **深度學習的數學基礎**。建議參考 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 的 [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)，該書也可在線獲取：[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
* **人工智能在商業中的應用案例**。建議參加 [商業用戶的人工智能入門](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，或由 [INSEAD](https://www.insead.edu/) 合作開發的 [AI 商業學院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)。
* **經典機器學習**，這在我們的 [機器學習入門課程](http://github.com/Microsoft/ML-for-Beginners) 中有詳細描述。
* 使用 **[認知服務](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** 構建的實際人工智能應用。建議從 Microsoft Learn 的模組開始，例如 [視覺](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然語言處理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[Azure OpenAI Service 的生成式人工智能](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 等。
* 特定的機器學習 **雲框架**，例如 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) 或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。建議參加 [使用 Azure Machine Learning 構建和運營機器學習解決方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 和 [使用 Azure Databricks 構建和運營機器學習解決方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
* **對話式人工智能** 和 **聊天機器人**。有一個單獨的 [創建對話式人工智能解決方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，您也可以參考 [這篇博客文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) 了解更多細節。
* **深度學習背後的數學**。建議參考 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 的 [深度學習](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)，該書也可在線獲得：[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
如果您想對 _雲端 AI_ 主題有一個簡單的入門，可以考慮參加 [在 Azure 上開始人工智能之旅](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
如果您想要溫和地了解 _雲端人工智能_ 主題，可以考慮參加 [在 Azure 上開始人工智能](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
# 課程內容
| | 課程連結 | PyTorch/Keras/TensorFlow | 實驗室 |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [課程設置](./lessons/0-course-setup/setup.md) | [設置您的開發環境](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI 簡介**](./lessons/1-Intro/README.md) | | |
| 01 | [AI 的簡介與歷史](./lessons/1-Intro/README.md) | - | - |
| II | **符號 AI** |
| I | [**人工智能簡介**](./lessons/1-Intro/README.md) | | |
| 01 | [人工智能的簡介與歷史](./lessons/1-Intro/README.md) | - | - |
| II | **符號人工智能** |
| 02 | [知識表示與專家系統](./lessons/2-Symbolic/README.md) | [專家系統](./lessons/2-Symbolic/Animals.ipynb) / [本體論](./lessons/2-Symbolic/FamilyOntology.ipynb) /[概念圖](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**神經網絡簡介**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [感知器](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [筆記本](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [實驗室](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [多層感知器與創建我們自己的框架](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [筆記本](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [實驗室](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [框架介紹 (PyTorch/TensorFlow) 及過度擬合](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [實驗室](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**電腦視覺**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [探索 Microsoft Azure 的電腦視覺](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [電腦視覺介紹. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [筆記本](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [實驗室](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 05 | [框架入門（PyTorch/TensorFlow）及過度擬合](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [實驗室](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**電腦視覺**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [探索 Microsoft Azure 上的電腦視覺](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [電腦視覺入門. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [筆記本](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [實驗室](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [卷積神經網絡](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN 架構](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [實驗室](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [預訓練網絡及遷移學習](./lessons/4-ComputerVision/08-TransferLearning/README.md) 和 [訓練技巧](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [實驗室](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [自編碼器及變分自編碼器 (VAEs)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [生成對抗網絡 (GANs) 及藝術風格轉移](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 09 | [自編碼器及 VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [生成對抗網絡及藝術風格遷移](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [物件檢測](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [實驗室](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [語義分割. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**自然語言處理**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [探索 Microsoft Azure 的自然語言處理](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [文本表示. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [語義詞嵌入. Word2Vec 和 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [語言建模. 訓練自己的嵌入](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [實驗室](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [循環神經網絡 (RNN)](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成型循環網絡](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [實驗室](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [變壓器. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [命名實體識別 (NER)](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [實驗室](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大型語言模型, 提示編程及少樣本任務](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**自然語言處理**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [探索 Microsoft Azure 上的自然語言處理](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [文本表示. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [語義詞嵌入. Word2Vec 和 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [語言建模. 訓練自己的嵌入](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [實驗室](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [循環神經網絡](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成循環網絡](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [實驗室](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformer. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [命名實體識別](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [實驗室](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大型語言模型、提示編程及少樣本任務](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **其他 AI 技術** || |
| 21 | [遺傳算法](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [筆記本](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [深度強化學習](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [實驗室](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [多代理系統](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI 倫理** | | |
| 24 | [AI 倫理及負責任的 AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: 負責任的 AI 原則](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **附加內容** | | |
| 25 | [多模態網絡, CLIP 和 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [筆記本](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| IX | **額外內容** | | |
| 25 | [多模態網絡、CLIP 和 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [筆記本](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## 每節課包含
* 預讀材料
* 可執行的 Jupyter 筆記本，通常針對特定框架（**PyTorch** 或 **TensorFlow**）。可執行的筆記本還包含大量理論材料，因此要理解主題，您需要至少完成一個版本的筆記本（PyTorch 或 TensorFlow）。
* **實驗室**（部分主題提供），讓您有機會將所學應用於特定問題。
* 部分章節包含指向 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模組的鏈接，涵蓋相關主題。
* 預讀材料
* 可執行的 Jupyter 筆記本，通常針對框架（**PyTorch** 或 **TensorFlow**）。可執行的筆記本還包含大量理論材料，因此要理解主題，您需要至少完成一個版本的筆記本（PyTorch 或 TensorFlow）。
* **實驗室**（部分主題提供），讓您有機會將所學材料應用於特定問題。
* 部分章節包含指向 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模組的連結，涵蓋相關主題。
## 開始學習
- 我們已創建 [設置課程](./lessons/0-course-setup/setup.md) 幫助您設置開發環境。
- 對於教育工作者，我們還創建了 [課程設置指南](./lessons/0-course-setup/for-teachers.md)。
- 我們已創建 [設置課程](./lessons/0-course-setup/setup.md)，幫助您設置開發環境。 - 對於教育工作者，我們也創建了 [課程設置指南](./lessons/0-course-setup/for-teachers.md)！
- 如何 [在 VSCode 或 Codepace 中運行代碼](./lessons/0-course-setup/how-to-run.md)
請按照以下步驟操作：
請按照以下步驟：
1. Fork 此倉庫：點擊頁面右上角的 "Fork" 按鈕。
2. 克隆倉庫：`git clone https://github.com/microsoft/AI-For-Beginners.git`
3. 別忘了給此倉庫加星標 (🌟)，以便日後更容易找到。
Fork 此倉庫：點擊頁面右上角的 "Fork" 按鈕。
## 與其他學員交流
克隆倉庫：`git clone https://github.com/microsoft/AI-For-Beginners.git`
加入我們的 [官方 AI Discord 伺服器](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)，與其他學員交流並獲得支持。
別忘了給此倉庫加星（🌟），方便日後找到。
如果您在構建過程中有產品反饋或問題，請訪問我們的 [Azure AI Foundry 開發者論壇](https://aka.ms/foundry/forum)。
## 與其他學習者交流
加入我們的 [官方 AI Discord 伺服器](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)，與其他學習者交流並獲得支持。
如果您在構建過程中有產品反饋或問題，請訪問我們的 [Azure AI Foundry 開發者論壇](https://aka.ms/foundry/forum)
## 測驗
> **關於測驗的注意事項**：所有測驗都存放在 etc\quiz-app 的 Quiz-app 資料夾中，或者可以在[線上查看](https://ff-quizzes.netlify.app/)。測驗已在課程中連結，測驗應用程式可以在本地執行或部署到 Azure；請按照 `quiz-app` 資料夾中的指示操作。測驗正在逐步進行本地化。
## 幫助需求
> **關於測驗的注意事項**：所有測驗都存放在 etc\quiz-app 的 Quiz-app 資料夾中，或者可以在[線上查看](https://ff-quizzes.netlify.app/)。測驗已經在課程中進行了連結，測驗應用程式可以在本地執行或部署到 Azure；請按照 `quiz-app` 資料夾中的指示操作。測驗正在逐步進行本地化。
## 尋求幫助
你有任何建議，或者發現拼寫或程式碼錯誤嗎？請提交一個 issue 或建立一個 pull request。
有任何建議或發現拼寫或程式碼錯誤？請提出問題或建立拉取請求。
## 特別鳴謝
## 特別感謝
* **✍️ 主要作者：** [Dmitry Soshnikov](http://soshnikov.com)，博士
* **🔥 編輯：** [Jen Looper](https://twitter.com/jenlooper)，博士
* **🎨 插畫設計：** [Tomomi Imura](https://twitter.com/girlie_mac)
* **🎨 手繪筆記插畫師：** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ 測驗創作者：** [Lateefah Bello](https://github.com/CinnamonXI)，[MLSA](https://studentambassadors.microsoft.com/)
* **🙏 核心貢獻者：** [Evgenii Pishchik](https://github.com/Pe4enIks)
## 其他課程
我們的團隊還製作了其他課程！請查看以下內容：
我們的團隊還製作了其他課程！查看以下內容：
- [初學者生成式 AI](https://aka.ms/genai-beginners)
- [初學者生成式 AI .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [生成式 AI 初學者課程](https://aka.ms/genai-beginners)
- [生成式 AI 初學者課程 .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [使用 JavaScript 的生成式 AI](https://github.com/microsoft/generative-ai-with-javascript)
- [使用 Java 的生成式 AI](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [初學者 AI](https://aka.ms/ai-beginners)
- [初學者數據科學](https://aka.ms/datascience-beginners)
- [初學者機器學習](https://aka.ms/ml-beginners)
- [初學者網絡安全](https://github.com/microsoft/Security-101)
- [初學者網頁開發](https://aka.ms/webdev-beginners)
- [初學者物聯網](https://aka.ms/iot-beginners)
- [初學者 XR 開發](https://github.com/microsoft/xr-development-for-beginners)
- [精通 GitHub Copilot 的智能應用](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [精通 GitHub Copilot 的 C#/.NET 開發者](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [AI 初學者課程](https://aka.ms/ai-beginners)
- [資料科學初學者課程](https://aka.ms/datascience-beginners)
- [機器學習初學者課程](https://aka.ms/ml-beginners)
- [網絡安全初學者課程](https://github.com/microsoft/Security-101)
- [網頁開發初學者課程](https://aka.ms/webdev-beginners)
- [物聯網初學者課程](https://aka.ms/iot-beginners)
- [XR 開發初學者課程](https://github.com/microsoft/xr-development-for-beginners)
- [精通 GitHub Copilot 用於代理性使用](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [精通 GitHub Copilot 用於 C#/.NET 開發者](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [選擇你的 Copilot 冒險](https://github.com/microsoft/CopilotAdventures)
---
**免責聲明**：
本文件已使用人工智能翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。儘管我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。原始文件的母語版本應被視為權威來源。對於重要信息，建議使用專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解釋概不負責。
此文件已使用 AI 翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原始語言的文件作為權威來源。對於關鍵資訊，建議尋求專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解讀概不負責。

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@ -1,8 +1,8 @@
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@ -25,17 +25,17 @@ CO_OP_TRANSLATOR_METADATA:
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.hr.png)|
|:---:|
| AI za početnike - _Sketchnote od [@girlie_mac](https://twitter.com/girlie_mac)_ |
| AI za početnike - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ |
Istražite svijet **umjetne inteligencije** (AI) uz naš 12-tjedni kurikulum s 24 lekcije! Uključuje praktične lekcije, kvizove i laboratorijske vježbe. Kurikulum je prilagođen početnicima i pokriva alate poput TensorFlowa i PyTorcha, kao i etiku u AI-ju.
Istražite svijet **umjetne inteligencije** (AI) uz naš 12-tjedni kurikulum koji se sastoji od 24 lekcije! Uključuje praktične lekcije, kvizove i laboratorijske vježbe. Kurikulum je prilagođen početnicima i pokriva alate poput TensorFlow-a i PyTorch-a, kao i etiku u AI.
### 🌐 Podrška za više jezika
#### Podržano putem GitHub Action (Automatizirano i uvijek ažurirano)
#### Podržano putem GitHub Action (Automatski i uvijek ažurirano)
[Francuski](../fr/README.md) | [Španjolski](../es/README.md) | [Njemački](../de/README.md) | [Ruski](../ru/README.md) | [Arapski](../ar/README.md) | [Perzijski (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Kineski (pojednostavljeni)](../zh/README.md) | [Kineski (tradicionalni, Makao)](../mo/README.md) | [Kineski (tradicionalni, Hong Kong)](../hk/README.md) | [Kineski (tradicionalni, Tajvan)](../tw/README.md) | [Japanski](../ja/README.md) | [Korejski](../ko/README.md) | [Hindski](../hi/README.md) | [Bengalski](../bn/README.md) | [Marathi](../mr/README.md) | [Nepalski](../ne/README.md) | [Pandžapski (Gurmukhi)](../pa/README.md) | [Portugalski (Portugal)](../pt/README.md) | [Portugalski (Brazil)](../br/README.md) | [Talijanski](../it/README.md) | [Poljski](../pl/README.md) | [Turski](../tr/README.md) | [Grčki](../el/README.md) | [Tajlandski](../th/README.md) | [Švedski](../sv/README.md) | [Danski](../da/README.md) | [Norveški](../no/README.md) | [Finski](../fi/README.md) | [Nizozemski](../nl/README.md) | [Hebrejski](../he/README.md) | [Vijetnamski](../vi/README.md) | [Indonezijski](../id/README.md) | [Malajski](../ms/README.md) | [Tagalog (Filipinski)](../tl/README.md) | [Svahili](../sw/README.md) | [Mađarski](../hu/README.md) | [Češki](../cs/README.md) | [Slovački](../sk/README.md) | [Rumunjski](../ro/README.md) | [Bugarski](../bg/README.md) | [Srpski (ćirilica)](../sr/README.md) | [Hrvatski](./README.md) | [Slovenski](../sl/README.md) | [Ukrajinski](../uk/README.md) | [Burmanski (Mjanmar)](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](./README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Ako želite dodati dodatne jezike, podržani jezici navedeni su [ovdje](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Ako želite dodati podršku za dodatne jezike, popis podržanih jezika možete pronaći [ovdje](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Pridružite se zajednici
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -47,73 +47,73 @@ Istražite svijet **umjetne inteligencije** (AI) uz naš 12-tjedni kurikulum s 2
U ovom kurikulumu naučit ćete:
* Različite pristupe umjetnoj inteligenciji, uključujući "dobri stari" simbolički pristup s **reprezentacijom znanja** i zaključivanjem ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neuronske mreže** i **duboko učenje**, koji su u središtu moderne AI tehnologije. Koncepte iza ovih važnih tema ilustrirat ćemo kodom u dva najpopularnija okvira - [TensorFlow](http://Tensorflow.org) i [PyTorch](http://pytorch.org).
* **Neuronske arhitekture** za rad sa slikama i tekstom. Pokrit ćemo nedavne modele, ali možda nećemo obuhvatiti najnovije stanje tehnologije.
* **Neuralne mreže** i **duboko učenje**, koji su srž moderne AI. Ilustrirat ćemo koncepte iza ovih važnih tema koristeći kod u dva najpopularnija okvira - [TensorFlow](http://Tensorflow.org) i [PyTorch](http://pytorch.org).
* **Neuralne arhitekture** za rad s slikama i tekstom. Pokrit ćemo nedavne modele, ali možda nećemo obuhvatiti najnovije dostignuće.
* Manje popularne AI pristupe, poput **genetskih algoritama** i **sustava s više agenata**.
Što nećemo pokriti u ovom kurikulumu:
> [Pronađite sve dodatne resurse za ovaj tečaj u našoj Microsoft Learn kolekciji](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Poslovne slučajeve korištenja **AI u poslovanju**. Razmotrite pohađanje [Uvod u AI za poslovne korisnike](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) na Microsoft Learn platformi ili [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), razvijene u suradnji s [INSEAD](https://www.insead.edu/).
* **Klasično strojno učenje**, koje je dobro opisano u našem [Kurikulumu za strojno učenje za početnike](http://github.com/Microsoft/ML-for-Beginners).
* Praktične AI aplikacije izgrađene pomoću **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Za ovo preporučujemo početak s modulima Microsoft Learn za [viziju](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [obradu prirodnog jezika](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generativni AI s Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** i druge.
* Specifične ML **Cloud Frameworks**, poput [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) ili [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Razmotrite korištenje [Izgradnja i upravljanje rješenjima za strojno učenje s Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) i [Izgradnja i upravljanje rješenjima za strojno učenje s Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Konverzacijski AI** i **Chat Botovi**. Postoji zaseban [Kreiranje rješenja za konverzacijski AI](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) tečaj, a možete se također referirati na [ovaj blog post](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) za više detalja.
* **Duboka matematika** iza dubokog učenja. Za ovo bismo preporučili knjigu [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) autora Iana Goodfellowa, Yoshue Bengioa i Aarona Courvillea, koja je također dostupna online na [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Poslovne slučajeve korištenja **AI u poslovanju**. Razmislite o pohađanju [Uvod u AI za poslovne korisnike](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) na Microsoft Learn ili [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), razvijen u suradnji s [INSEAD](https://www.insead.edu/).
* **Klasično strojno učenje**, koje je dobro opisano u našem [Kurikulumu za početnike u strojnom učenju](http://github.com/Microsoft/ML-for-Beginners).
* Praktične AI aplikacije izgrađene koristeći **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Za ovo preporučujemo da započnete s modulima Microsoft Learn za [viziju](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [obradu prirodnog jezika](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generativna AI s Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** i druge.
* Specifične ML **Cloud Frameworks**, poput [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) ili [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Razmislite o korištenju [Izgradnja i upravljanje rješenjima za strojno učenje s Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) i [Izgradnja i upravljanje rješenjima za strojno učenje s Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) kurikuluma.
* **Konverzacijska AI** i **Chat Botovi**. Postoji zaseban [Izradite rješenja za konverzacijski AI](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) kurikulum, a možete se također referirati na [ovaj blog post](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) za više detalja.
* **Duboka matematika** iza dubokog učenja. Za ovo preporučujemo [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) od Iana Goodfellowa, Yoshue Bengio i Aarona Courvillea, koja je također dostupna online na [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Za blagi uvod u teme _AI u oblaku_ možete razmotriti pohađanje [Uvod u umjetnu inteligenciju na Azureu](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) tečaja.
Za blagi uvod u _AI u oblaku_ teme, razmislite o pohađanju [Započnite s umjetnom inteligencijom na Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) kurikuluma.
# Sadržaj
| | Poveznica na lekciju | PyTorch/Keras/TensorFlow | Laboratorij |
| | Link lekcije | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Postavljanje tečaja](./lessons/0-course-setup/setup.md) | [Postavite svoje razvojno okruženje](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Uvod u AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Uvod i povijest AI-ja](./lessons/1-Intro/README.md) | - | - |
| II | **Simbolički AI** |
| 01 | [Uvod i povijest AI](./lessons/1-Intro/README.md) | - | - |
| II | **Simbolička AI** |
| 02 | [Reprezentacija znanja i ekspertni sustavi](./lessons/2-Symbolic/README.md) | [Ekspertni sustavi](./lessons/2-Symbolic/Animals.ipynb) / [Ontologija](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Konceptualni graf](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Uvod u neuronske mreže**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Laboratorij](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Višeslojni perceptron i stvaranje vlastitog okvira](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Laboratorij](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| III | [**Uvod u neuralne mreže**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Višeslojni perceptron i stvaranje vlastitog okvira](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Uvod u okvire (PyTorch/TensorFlow) i prenaučavanje](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorij](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Računalni vid**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Istražite računalni vid na Microsoft Azureu](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| IV | [**Računalni vid**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Istražite računalni vid na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Uvod u računalni vid. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Bilježnica](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Laboratorij](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvolucijske neuronske mreže](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Arhitekture CNN-a](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Laboratorij](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Unaprijed istrenirane mreže i prijenosno učenje](./lessons/4-ComputerVision/08-TransferLearning/README.md) i [Trikovi za treniranje](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorij](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoenkoderi i VAE](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 08 | [Predtrenirane mreže i prijenos učenja](./lessons/4-ComputerVision/08-TransferLearning/README.md) i [Trikovi za treniranje](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorij](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoenkoderi i VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generativne suparničke mreže i prijenos umjetničkog stila](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Detekcija objekata](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Laboratorij](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantička segmentacija. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Obrada prirodnog jezika**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Istražite obradu prirodnog jezika na Microsoft Azureu](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Reprezentacija teksta. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantičke ugrađenosti riječi. Word2Vec i GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Jezično modeliranje. Treniranje vlastitih ugrađenosti](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratorij](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurentne neuronske mreže](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generativne rekurentne mreže](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Laboratorij](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformeri. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Prepoznavanje imenovanih entiteta](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratorij](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Veliki jezični modeli, programski upiti i zadaci s malo primjera](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**Obrada prirodnog jezika**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Istražite obradu prirodnog jezika na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Reprezentacija teksta. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantičke reprezentacije riječi. Word2Vec i GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modeliranje jezika. Treniranje vlastitih reprezentacija](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratorij](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurzivne neuronske mreže](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generativne rekurzivne mreže](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Laboratorij](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformeri. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Prepoznavanje imenovanih entiteta](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratorij](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Veliki jezični modeli, programiranje upita i zadaci s malo primjera](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Ostale AI tehnike** || |
| 21 | [Genetski algoritmi](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Bilježnica](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Duboko pojačano učenje](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Laboratorij](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Sustavi s više agenata](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI etika** | | |
| 24 | [AI etika i odgovorna umjetna inteligencija](./lessons/7-Ethics/README.md) | [Microsoft Learn: Načela odgovorne AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| VII | **Etika AI-a** | | |
| 24 | [Etika AI-a i odgovorni AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Principi odgovornog AI-a](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Dodaci** | | |
| 25 | [Višemodalne mreže, CLIP i VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Bilježnica](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 25 | [Mreže s više modaliteta, CLIP i VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Bilježnica](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Svaka lekcija sadrži
* Materijale za prethodno čitanje
* Izvršne Jupyter bilježnice, koje su često specifične za određeni okvir (**PyTorch** ili **TensorFlow**). Izvršna bilježnica također sadrži mnogo teorijskog materijala, pa je za razumijevanje teme potrebno proći barem jednu verziju bilježnice (bilo PyTorch ili TensorFlow).
* **Laboratorije** dostupne za neke teme, koji vam pružaju priliku da primijenite naučeno na specifičan problem.
* Neki odjeljci sadrže poveznice na module [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) koji pokrivaju srodne teme.
* Materijale za predčitanje
* Izvršne Jupyter bilježnice, koje su često specifične za okvir (**PyTorch** ili **TensorFlow**). Izvršna bilježnica također sadrži mnogo teorijskog materijala, pa da biste razumjeli temu, trebate proći barem jednu verziju bilježnice (bilo PyTorch ili TensorFlow).
* **Laboratoriji** dostupni za neke teme, koji vam pružaju priliku da primijenite naučeno na specifičan problem.
* Neki odjeljci sadrže poveznice na [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) module koji pokrivaju povezane teme.
## Početak
## Početak rada
- Pripremili smo [lekciju za postavljanje](./lessons/0-course-setup/setup.md) kako bismo vam pomogli u postavljanju vašeg razvojnog okruženja. - Za edukatore, pripremili smo i [lekciju za postavljanje kurikuluma](./lessons/0-course-setup/for-teachers.md)!
- Kako [pokrenuti kod u VSCode ili Codepaceu](./lessons/0-course-setup/how-to-run.md)
- Kreirali smo [lekciju za postavljanje](./lessons/0-course-setup/setup.md) kako bismo vam pomogli u postavljanju vašeg razvojnog okruženja. - Za edukatore, kreirali smo i [lekciju za postavljanje kurikuluma](./lessons/0-course-setup/for-teachers.md)!
- Kako [pokrenuti kod u VSCode ili Codepace](./lessons/0-course-setup/how-to-run.md)
Slijedite ove korake:
@ -123,46 +123,46 @@ Klonirajte repozitorij: `git clone https://github.com/microsoft/AI-For-Beginners
Ne zaboravite označiti (🌟) ovaj repozitorij kako biste ga kasnije lakše pronašli.
## Upoznajte druge učenike
## Upoznajte druge polaznike
Pridružite se našem [službenom AI Discord serveru](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) kako biste upoznali i povezali se s drugim učenicima koji pohađaju ovaj tečaj i dobili podršku.
Pridružite se našem [službenom AI Discord serveru](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) kako biste upoznali i povezali se s drugim polaznicima ovog tečaja te dobili podršku.
Ako imate povratne informacije o proizvodu ili pitanja tijekom izrade, posjetite naš [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Kvizovi
> **Napomena o kvizovima**: Svi kvizovi nalaze se u mapi Quiz-app u etc\quiz-app, ili [Online Ovdje](https://ff-quizzes.netlify.app/). Povezani su unutar lekcija, a aplikacija za kviz može se pokrenuti lokalno ili implementirati na Azure; slijedite upute u mapi `quiz-app`. Postupno se lokaliziraju.
## Potrebna Pomoć
## Traži se pomoć
Imate li prijedloge ili ste pronašli pravopisne ili programske pogreške? Otvorite problem ili kreirajte pull request.
## Posebna Zahvala
## Posebne zahvale
* **✍️ Glavni Autor:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Urednica:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustrator sketchnoteova:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Kreator kvizova:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Glavni Suradnici:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ Glavni autor:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Urednica:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustrator sketchnoteova:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Kreator kvizova:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Glavni suradnici:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Ostali Kurikulumi
## Ostali kurikulumi
Naš tim izrađuje i druge kurikulume! Pogledajte:
Naš tim proizvodi i druge kurikulume! Pogledajte:
- [Generativna AI za Početnike](https://aka.ms/genai-beginners)
- [Generativna AI za Početnike .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generativna AI s JavaScriptom](https://github.com/microsoft/generative-ai-with-javascript)
- [Generativna AI s Javom](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI za Početnike](https://aka.ms/ai-beginners)
- [Data Science za Početnike](https://aka.ms/datascience-beginners)
- [Strojno Učenje za Početnike](https://aka.ms/ml-beginners)
- [Kibernetička Sigurnost za Početnike](https://github.com/microsoft/Security-101)
- [Web Razvoj za Početnike](https://aka.ms/webdev-beginners)
- [IoT za Početnike](https://aka.ms/iot-beginners)
- [XR Razvoj za Početnike](https://github.com/microsoft/xr-development-for-beginners)
- [Ovladavanje GitHub Copilotom za Agentnu Upotrebu](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Ovladavanje GitHub Copilotom za C#/.NET Razvijače](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Odaberite Svoju Vlastitu Copilot Avanturu](https://github.com/microsoft/CopilotAdventures)
- [Generativna AI za početnike](https://aka.ms/genai-beginners)
- [Generativna AI za početnike .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generativna AI s JavaScriptom](https://github.com/microsoft/generative-ai-with-javascript)
- [Generativna AI s Javom](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI za početnike](https://aka.ms/ai-beginners)
- [Data Science za početnike](https://aka.ms/datascience-beginners)
- [ML za početnike](https://aka.ms/ml-beginners)
- [Kibernetička sigurnost za početnike](https://github.com/microsoft/Security-101)
- [Web razvoj za početnike](https://aka.ms/webdev-beginners)
- [IoT za početnike](https://aka.ms/iot-beginners)
- [XR razvoj za početnike](https://github.com/microsoft/xr-development-for-beginners)
- [Ovladavanje GitHub Copilotom za agentičku upotrebu](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Ovladavanje GitHub Copilotom za C#/.NET programere](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Odaberi svoju Copilot avanturu](https://github.com/microsoft/CopilotAdventures)
---
**Odricanje od odgovornosti**:
Ovaj dokument je preveden korištenjem AI usluge za prevođenje [Co-op Translator](https://github.com/Azure/co-op-translator). Iako nastojimo osigurati točnost, imajte na umu da automatski prijevodi mogu sadržavati pogreške ili netočnosti. Izvorni dokument na izvornom jeziku treba smatrati mjerodavnim izvorom. Za ključne informacije preporučuje se profesionalni prijevod od strane stručnjaka. Ne preuzimamo odgovornost za bilo kakva nesporazuma ili pogrešna tumačenja koja mogu proizaći iz korištenja ovog prijevoda.
Ovaj dokument je preveden pomoću AI usluge za prevođenje [Co-op Translator](https://github.com/Azure/co-op-translator). Iako nastojimo osigurati točnost, imajte na umu da automatski prijevodi mogu sadržavati pogreške ili netočnosti. Izvorni dokument na izvornom jeziku treba smatrati autoritativnim izvorom. Za ključne informacije preporučuje se profesionalni prijevod od strane ljudskog prevoditelja. Ne preuzimamo odgovornost za nesporazume ili pogrešne interpretacije koje mogu proizaći iz korištenja ovog prijevoda.

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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Mesterséges Intelligencia Kezdőknek - Tananyag
# Mesterséges Intelligencia Kezdőknek - Tananyag
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.hu.png)|
|:---:|
| AI Kezdőknek - _Sketchnote készítette: [@girlie_mac](https://twitter.com/girlie_mac)_ |
Fedezd fel a **Mesterséges Intelligencia** (MI) világát 12 hetes, 24 leckéből álló tananyagunkkal! Gyakorlati órákat, kvízeket és laborokat tartalmaz. A tananyag kezdőbarát, és olyan eszközöket mutat be, mint a TensorFlow és PyTorch, valamint az MI etikai kérdéseit is tárgyalja.
Fedezd fel a **Mesterséges Intelligencia** (MI) világát 12 hetes, 24 leckéből álló tananyagunkkal! Gyakorlati órákat, kvízeket és laborokat tartalmaz. A tananyag kezdőbarát, és olyan eszközöket is bemutat, mint a TensorFlow és PyTorch, valamint az MI etikai kérdéseit.
### 🌐 Többnyelvű támogatás
### 🌐 Többnyelvű támogatás
#### GitHub Action segítségével (Automatikus és mindig naprakész)
#### GitHub Action segítségével (Automatikus és mindig naprakész)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](./README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
[Francia](../fr/README.md) | [Spanyol](../es/README.md) | [Német](../de/README.md) | [Orosz](../ru/README.md) | [Arab](../ar/README.md) | [Perzsa (Fárszi)](../fa/README.md) | [Urdu](../ur/README.md) | [Kínai (Egyszerűsített)](../zh/README.md) | [Kínai (Hagyományos, Makaó)](../mo/README.md) | [Kínai (Hagyományos, Hongkong)](../hk/README.md) | [Kínai (Hagyományos, Tajvan)](../tw/README.md) | [Japán](../ja/README.md) | [Koreai](../ko/README.md) | [Hindi](../hi/README.md) | [Bengáli](../bn/README.md) | [Maráthi](../mr/README.md) | [Nepáli](../ne/README.md) | [Pandzsábi (Gurmukhi)](../pa/README.md) | [Portugál (Portugália)](../pt/README.md) | [Portugál (Brazília)](../br/README.md) | [Olasz](../it/README.md) | [Lengyel](../pl/README.md) | [Török](../tr/README.md) | [Görög](../el/README.md) | [Thai](../th/README.md) | [Svéd](../sv/README.md) | [Dán](../da/README.md) | [Norvég](../no/README.md) | [Finn](../fi/README.md) | [Holland](../nl/README.md) | [Héber](../he/README.md) | [Vietnámi](../vi/README.md) | [Indonéz](../id/README.md) | [Maláj](../ms/README.md) | [Tagalog (Filippínó)](../tl/README.md) | [Szuahéli](../sw/README.md) | [Magyar](./README.md) | [Cseh](../cs/README.md) | [Szlovák](../sk/README.md) | [Román](../ro/README.md) | [Bolgár](../bg/README.md) | [Szerb (Cirill)](../sr/README.md) | [Horvát](../hr/README.md) | [Szlovén](../sl/README.md) | [Ukrán](../uk/README.md) | [Burmai (Mianmar)](../my/README.md)
**Ha további fordításokat szeretnél, a támogatott nyelvek listája [itt található](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Ha további nyelveken szeretnéd látni a fordítást, a támogatott nyelvek listája [itt található](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Csatlakozz a közösséghez
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Amit megtanulsz
## Amit megtanulsz
**[A tanfolyam gondolattérképe](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[A kurzus gondolattérképe](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
Ebben a tananyagban megtanulhatod:
* A mesterséges intelligencia különböző megközelítéseit, beleértve a "régi jó" szimbolikus megközelítést **Tudásreprezentációval** és következtetéssel ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neurális hálózatokat** és **mélytanulást**, amelyek a modern MI alapját képezik. Ezeket a fontos témákat két népszerű keretrendszer - [TensorFlow](http://Tensorflow.org) és [PyTorch](http://pytorch.org) - kódjával illusztráljuk.
* **Neurális architektúrákat** képek és szövegek feldolgozásához. Bár a legújabb modelleket tárgyaljuk, lehet, hogy nem teljesen naprakészek.
* **Neurális architektúrákat** képek és szövegek feldolgozásához. Bár a legújabb modelleket bemutatjuk, lehet, hogy nem teljesen naprakészek.
* Kevésbé népszerű MI megközelítéseket, mint például **Genetikus algoritmusok** és **Multi-Agent rendszerek**.
Amit nem tárgyalunk ebben a tananyagban:
Amit nem fogunk lefedni ebben a tananyagban:
> [Az összes további forrást megtalálod a Microsoft Learn gyűjteményünkben](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Az összes további forrást megtalálod a kurzushoz a Microsoft Learn gyűjteményünkben](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Az MI üzleti alkalmazásait. Javasoljuk, hogy vegyél részt az [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) tanfolyamon a Microsoft Learn platformon, vagy az [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) programon, amelyet az [INSEAD](https://www.insead.edu/) közreműködésével fejlesztettek ki.
* **Klasszikus gépi tanulás**, amelyet részletesen bemutatunk a [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners) tananyagunkban.
* Gyakorlati MI alkalmazások, amelyek **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** segítségével készültek. Ehhez javasoljuk, hogy kezdj a Microsoft Learn moduljaival, például [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** és mások.
* Specifikus ML **felhőkeretrendszerek**, mint például [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), vagy [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Javasoljuk, hogy vegyél részt a [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) és [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) tanfolyamokon.
* **Beszélgető MI** és **Chatbotok**. Külön tanfolyamot találsz a [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) témában, valamint további részleteket [ebben a blogbejegyzésben](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/).
* **Mély matematikai alapok** a mélytanulás mögött. Ehhez ajánljuk Ian Goodfellow, Yoshua Bengio és Aaron Courville [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) című könyvét, amely online is elérhető [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) címen.
* **Üzleti esetek** az MI üzleti alkalmazásairól. Javasoljuk, hogy vegyél részt a [Bevezetés az MI-be üzleti felhasználók számára](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) tanulási útvonalon a Microsoft Learn-en, vagy az [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) programon, amelyet az [INSEAD](https://www.insead.edu/) közreműködésével fejlesztettek ki.
* **Klasszikus gépi tanulás**, amelyet részletesen bemutatunk a [Gépi tanulás kezdőknek tananyagunkban](http://github.com/Microsoft/ML-for-Beginners).
* Gyakorlati MI alkalmazások, amelyek **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** segítségével készültek. Ehhez javasoljuk, hogy kezdj a Microsoft Learn moduljaival, például [látás](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [természetes nyelvfeldolgozás](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generatív MI az Azure OpenAI Service segítségével](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** és mások.
* Specifikus ML **felhőkeretrendszerek**, mint például [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), vagy [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Javasoljuk, hogy vegyél részt a [Gépi tanulási megoldások építése és működtetése az Azure Machine Learning segítségével](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) és [Gépi tanulási megoldások építése és működtetése az Azure Databricks segítségével](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) tanulási útvonalakon.
* **Beszélgetési MI** és **Chatbotok**. Van egy külön [Beszélgetési MI megoldások létrehozása](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) tanulási útvonal, és további részletekért [ezt a blogbejegyzést](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) is megnézheted.
* **Mély matematikai alapok** a mélytanulás mögött. Ehhez ajánljuk Ian Goodfellow, Yoshua Bengio és Aaron Courville [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) című könyvét, amely online is elérhető: [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Egy könnyed bevezetéshez az _MI a felhőben_ témákhoz javasoljuk, hogy vegyél részt a [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) tanfolyamon.
Egy könnyed bevezetéshez az _MI a felhőben_ témákhoz érdemes lehet részt venni a [Bevezetés a mesterséges intelligenciába az Azure-on](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) tanulási útvonalon.
# Tartalom
# Tartalom
| | Lecke Link | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Tanfolyam beállítása](./lessons/0-course-setup/setup.md) | [Fejlesztési környezet beállítása](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Bevezetés az MI-be**](./lessons/1-Intro/README.md) | | |
| 01 | [Bevezetés és az MI története](./lessons/1-Intro/README.md) | - | - |
| II | **Szimbolikus MI** |
| 02 | [Tudásreprezentáció és szakértői rendszerek](./lessons/2-Symbolic/README.md) | [Szakértői rendszerek](./lessons/2-Symbolic/Animals.ipynb) / [Ontológia](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Fogalomgrafikon](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Bevezetés a neurális hálózatokba**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Többrétegű perceptron és saját keretrendszer létrehozása](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Bevezetés a keretrendszerekbe (PyTorch/TensorFlow) és túltanulás](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Számítógépes látás**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Fedezd fel a számítógépes látást a Microsoft Azure-on](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Bevezetés a számítógépes látásba. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvolúciós neurális hálók](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN architektúrák](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Előre betanított hálók és transzfer tanulás](./lessons/4-ComputerVision/08-TransferLearning/README.md) és [Tanítási trükkök](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| | Lecke linkje | PyTorch/Keras/TensorFlow | Labor |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Kurzus beállítása](./lessons/0-course-setup/setup.md) | [Fejlesztési környezet beállítása](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Bevezetés az MI-be**](./lessons/1-Intro/README.md) | | |
| 01 | [Bevezetés és az MI története](./lessons/1-Intro/README.md) | - | - |
| II | **Szimbolikus MI** |
| 02 | [Tudásreprezentáció és szakértői rendszerek](./lessons/2-Symbolic/README.md) | [Szakértői rendszerek](./lessons/2-Symbolic/Animals.ipynb) / [Ontológia](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Fogalomgrafikon](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Bevezetés a neurális hálózatokba**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Labor](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Többrétegű perceptron és saját keretrendszer létrehozása](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Labor](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Bevezetés a keretrendszerekbe (PyTorch/TensorFlow) és a túltanulásba](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Gyakorlat](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Számítógépes látás**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Számítógépes látás felfedezése a Microsoft Azure-on](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Bevezetés a számítógépes látásba. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Jegyzetfüzet](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Gyakorlat](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvolúciós neurális hálók](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN architektúrák](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Gyakorlat](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Előre betanított hálók és transzfer tanulás](./lessons/4-ComputerVision/08-TransferLearning/README.md) és [Tanítási trükkök](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Gyakorlat](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoenkóderek és VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generatív ellenséges hálók és művészi stílusátvitel](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Objektumfelismerés](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 11 | [Objektumfelismerés](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Gyakorlat](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Szemantikus szegmentáció. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Természetes nyelvfeldolgozás**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Fedezd fel a természetes nyelvfeldolgozást a Microsoft Azure-on](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Szöveg reprezentáció. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Szemantikus szóbeágyazások. Word2Vec és GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Nyelvi modellezés. Saját beágyazások tanítása](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurzív neurális hálók](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatív rekurzív hálók](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transzformerek. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Név entitás felismerés](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Nagy nyelvi modellek, prompt programozás és kevés példás feladatok](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**Természetes nyelvfeldolgozás**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Természetes nyelvfeldolgozás felfedezése a Microsoft Azure-on](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Szöveg reprezentáció. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Szemantikus szóbeágyazások. Word2Vec és GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Nyelvi modellezés. Saját beágyazások tanítása](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Gyakorlat](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurzív neurális hálók](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatív rekurzív hálók](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Gyakorlat](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transzformerek. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Név entitás felismerés](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Gyakorlat](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Nagy nyelvi modellek, prompt programozás és kevés példás feladatok](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Egyéb AI technikák** || |
| 21 | [Genetikus algoritmusok](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Mély megerősítéses tanulás](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 21 | [Genetikus algoritmusok](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Jegyzetfüzet](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Mély megerősítéses tanulás](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Gyakorlat](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Többügynökös rendszerek](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI Etika** | | |
| 24 | [AI Etika és felelős AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Felelős AI alapelvek](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Extrák** | | |
| 25 | [Multi-modális hálók, CLIP és VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 25 | [Multi-modális hálók, CLIP és VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Jegyzetfüzet](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Minden lecke tartalmaz
## Minden lecke tartalmazza
* Előzetes olvasnivalót
* Futtatható Jupyter Notebookokat, amelyek gyakran keretrendszer-specifikusak (**PyTorch** vagy **TensorFlow**). A futtatható notebookok sok elméleti anyagot is tartalmaznak, így a téma megértéséhez legalább az egyik verziót (PyTorch vagy TensorFlow) át kell nézni.
* **Labok** néhány témához, amelyek lehetőséget adnak arra, hogy az elsajátított anyagot egy konkrét problémára alkalmazd.
* Néhány szekció tartalmaz linkeket [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) modulokhoz, amelyek kapcsolódó témákat fednek le.
* Előzetes olvasmányok
* Futtatható Jupyter jegyzetfüzetek, amelyek gyakran keretrendszer-specifikusak (**PyTorch** vagy **TensorFlow**). A jegyzetfüzetek sok elméleti anyagot is tartalmaznak, így a téma megértéséhez legalább az egyik verziót (PyTorch vagy TensorFlow) érdemes átnézni.
* **Gyakorlatok**, amelyek néhány témához elérhetők, és lehetőséget adnak az anyag alkalmazására egy konkrét problémán.
* Egyes szekciók hivatkozásokat tartalmaznak [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) modulokra, amelyek kapcsolódó témákat fednek le.
## Kezdés
- Létrehoztunk egy [beállítási leckét](./lessons/0-course-setup/setup.md), amely segít a fejlesztési környezet beállításában. - Oktatóknak létrehoztunk egy [tanterv beállítási leckét](./lessons/0-course-setup/for-teachers.md) is!
- Hogyan [futtasd a kódot VSCode-ban vagy Codepace-ben](./lessons/0-course-setup/how-to-run.md)
- Hogyan [futtasd a kódot VSCode-ban vagy CodeSpace-ben](./lessons/0-course-setup/how-to-run.md)
Kövesd ezeket a lépéseket:
Forkold a repót: Kattints a "Fork" gombra az oldal jobb felső sarkában.
Clone-old a repót: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Klónozd a repót: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Ne felejtsd el csillagozni (🌟) ezt a repót, hogy később könnyebben megtaláld.
## Találkozz más tanulókkal
Csatlakozz az [AI hivatalos Discord szerverünkhöz](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), hogy találkozz és kapcsolatot építs más tanulókkal, akik ezt a kurzust végzik, és támogatást kapj.
Csatlakozz a [hivatalos AI Discord szerverünkhöz](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), hogy találkozz és kapcsolatba lépj más tanulókkal, akik ezt a kurzust végzik, és támogatást kapj.
Ha termék visszajelzésed vagy kérdéseid vannak az építés során, látogasd meg az [Azure AI Foundry Developer Fórumot](https://aka.ms/foundry/forum)
Ha termék-visszajelzésed vagy kérdéseid vannak az építés során, látogasd meg az [Azure AI Foundry fejlesztői fórumot](https://aka.ms/foundry/forum).
## Kvízek
> **Megjegyzés a kvízekről**: Minden kvíz az etc\quiz-app mappában található, vagy [Online itt](https://ff-quizzes.netlify.app/). A leckékből érhetők el, a kvíz alkalmazás helyben futtatható vagy Azure-ra telepíthető; kövesd az `quiz-app` mappában található utasításokat. Folyamatosan lokalizálják őket.
> **Megjegyzés a kvízekről**: Minden kvíz az etc\quiz-app mappában található, vagy [Online itt](https://ff-quizzes.netlify.app/). A leckékből érhetők el, a kvíz alkalmazás helyben futtatható vagy Azure-ra telepíthető; kövesd az `quiz-app` mappában található utasításokat. Fokozatosan lokalizálásra kerülnek.
## Segítség Kérve
Van javaslatod, vagy találtál helyesírási vagy kódbeli hibát? Nyiss egy hibajegyet, vagy hozz létre egy pull requestet.
Van javaslatod, vagy találtál helyesírási vagy kódhibát? Nyiss egy hibajegyet, vagy hozz létre egy pull requestet.
## Külön Köszönet
## Különleges Köszönet
* **✍️ Elsődleges szerző:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **✍️ Fő Szerző:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Szerkesztő:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Sketchnote illusztrátor:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Kvíz készítő:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Fő közreműködők:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✅ Kvíz Készítő:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Fő Közreműködők:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Egyéb Tananyagok
Csapatunk más tananyagokat is készít! Nézd meg:
- [Generatív MI Kezdőknek](https://aka.ms/genai-beginners)
- [Generatív MI Kezdőknek .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generatív MI JavaScript-tel](https://github.com/microsoft/generative-ai-with-javascript)
- [Generatív MI Java-val](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [MI Kezdőknek](https://aka.ms/ai-beginners)
- [Generatív AI Kezdőknek](https://aka.ms/genai-beginners)
- [Generatív AI Kezdőknek .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generatív AI JavaScript-tel](https://github.com/microsoft/generative-ai-with-javascript)
- [Generatív AI Java-val](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI Kezdőknek](https://aka.ms/ai-beginners)
- [Adattudomány Kezdőknek](https://aka.ms/datascience-beginners)
- [Gépi Tanulás Kezdőknek](https://aka.ms/ml-beginners)
- [ML Kezdőknek](https://aka.ms/ml-beginners)
- [Kiberbiztonság Kezdőknek](https://github.com/microsoft/Security-101)
- [Webfejlesztés Kezdőknek](https://aka.ms/webdev-beginners)
- [IoT Kezdőknek](https://aka.ms/iot-beginners)
@ -164,5 +164,5 @@ Csapatunk más tananyagokat is készít! Nézd meg:
---
**Felelősségkizárás**:
Ez a dokumentum az [Co-op Translator](https://github.com/Azure/co-op-translator) AI fordítási szolgáltatás segítségével készült. Bár törekszünk a pontosságra, kérjük, vegye figyelembe, hogy az automatikus fordítások hibákat vagy pontatlanságokat tartalmazhatnak. Az eredeti dokumentum az eredeti nyelvén tekintendő hiteles forrásnak. Kritikus információk esetén javasolt a professzionális, emberi fordítás igénybevétele. Nem vállalunk felelősséget a fordítás használatából eredő félreértésekért vagy téves értelmezésekért.
**Felelősség kizárása**:
Ez a dokumentum az AI fordítási szolgáltatás [Co-op Translator](https://github.com/Azure/co-op-translator) segítségével lett lefordítva. Bár törekszünk a pontosságra, kérjük, vegye figyelembe, hogy az automatikus fordítások hibákat vagy pontatlanságokat tartalmazhatnak. Az eredeti dokumentum az eredeti nyelvén tekintendő hiteles forrásnak. Kritikus információk esetén javasolt professzionális emberi fordítást igénybe venni. Nem vállalunk felelősséget semmilyen félreértésért vagy téves értelmezésért, amely a fordítás használatából eredhet.

124
translations/id/README.md
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@ -1,8 +1,8 @@
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|:---:|
| AI Untuk Pemula - _Sketchnote oleh [@girlie_mac](https://twitter.com/girlie_mac)_ |
| AI untuk Pemula - _Sketchnote oleh [@girlie_mac](https://twitter.com/girlie_mac)_ |
Jelajahi dunia **Kecerdasan Buatan** (AI) dengan kurikulum 12 minggu dan 24 pelajaran kami! Kurikulum ini mencakup pelajaran praktis, kuis, dan laboratorium. Dirancang untuk pemula, kurikulum ini mencakup alat seperti TensorFlow dan PyTorch, serta etika dalam AI.
Jelajahi dunia **Kecerdasan Buatan** (AI) dengan kurikulum 12 minggu dan 24 pelajaran kami! Kurikulum ini mencakup pelajaran praktis, kuis, dan laboratorium. Materi ini ramah pemula dan mencakup alat seperti TensorFlow dan PyTorch, serta etika dalam AI.
### 🌐 Dukungan Multi-Bahasa
@ -37,63 +37,63 @@ Jelajahi dunia **Kecerdasan Buatan** (AI) dengan kurikulum 12 minggu dan 24 pela
**Jika Anda ingin menambahkan bahasa terjemahan lainnya, daftar bahasa yang didukung tersedia [di sini](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Bergabunglah dengan Komunitas
## Bergabung dengan Komunitas
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Apa yang akan Anda pelajari
## Apa yang Akan Anda Pelajari
**[Peta Pikiran Kursus](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
Dalam kurikulum ini, Anda akan mempelajari:
* Pendekatan berbeda terhadap Kecerdasan Buatan, termasuk pendekatan simbolik "lama yang baik" dengan **Representasi Pengetahuan** dan penalaran ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Jaringan Neural** dan **Pembelajaran Mendalam**, yang menjadi inti dari AI modern. Kami akan mengilustrasikan konsep di balik topik penting ini menggunakan kode dalam dua kerangka kerja paling populer - [TensorFlow](http://Tensorflow.org) dan [PyTorch](http://pytorch.org).
* **Arsitektur Neural** untuk bekerja dengan gambar dan teks. Kami akan membahas model terbaru tetapi mungkin sedikit kurang dalam hal teknologi mutakhir.
* Pendekatan berbeda terhadap Kecerdasan Buatan, termasuk pendekatan simbolik "lama" dengan **Representasi Pengetahuan** dan penalaran ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Jaringan Saraf** dan **Deep Learning**, yang menjadi inti dari AI modern. Kami akan mengilustrasikan konsep-konsep di balik topik penting ini menggunakan kode dalam dua kerangka kerja paling populer - [TensorFlow](http://Tensorflow.org) dan [PyTorch](http://pytorch.org).
* **Arsitektur Jaringan Saraf** untuk bekerja dengan gambar dan teks. Kami akan membahas model-model terbaru, meskipun mungkin tidak mencakup yang paling mutakhir.
* Pendekatan AI yang kurang populer, seperti **Algoritma Genetik** dan **Sistem Multi-Agen**.
Apa yang tidak akan kami bahas dalam kurikulum ini:
> [Temukan semua sumber daya tambahan untuk kursus ini dalam koleksi Microsoft Learn kami](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Temukan semua sumber tambahan untuk kursus ini di koleksi Microsoft Learn kami](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Kasus bisnis penggunaan **AI dalam Bisnis**. Pertimbangkan untuk mengikuti jalur pembelajaran [Pengantar AI untuk pengguna bisnis](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) di Microsoft Learn, atau [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), yang dikembangkan bekerja sama dengan [INSEAD](https://www.insead.edu/).
* **Pembelajaran Mesin Klasik**, yang dijelaskan dengan baik dalam [Kurikulum Pembelajaran Mesin untuk Pemula](http://github.com/Microsoft/ML-for-Beginners).
* Kasus bisnis penggunaan **AI dalam Bisnis**. Pertimbangkan untuk mengambil jalur pembelajaran [Pengenalan AI untuk pengguna bisnis](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) di Microsoft Learn, atau [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), yang dikembangkan bekerja sama dengan [INSEAD](https://www.insead.edu/).
* **Machine Learning Klasik**, yang dijelaskan dengan baik dalam [Kurikulum Machine Learning untuk Pemula](http://github.com/Microsoft/ML-for-Beginners).
* Aplikasi AI praktis yang dibangun menggunakan **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Untuk ini, kami merekomendasikan Anda memulai dengan modul Microsoft Learn untuk [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI dengan Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** dan lainnya.
* Kerangka kerja **Cloud ML** tertentu, seperti [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), atau [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Pertimbangkan untuk menggunakan jalur pembelajaran [Bangun dan operasikan solusi pembelajaran mesin dengan Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) dan [Bangun dan Operasikan Solusi Pembelajaran Mesin dengan Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI Percakapan** dan **Chat Bots**. Ada jalur pembelajaran terpisah [Buat solusi AI percakapan](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), dan Anda juga dapat merujuk ke [posting blog ini](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) untuk detail lebih lanjut.
* **Matematika Mendalam** di balik pembelajaran mendalam. Untuk ini, kami merekomendasikan [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) oleh Ian Goodfellow, Yoshua Bengio, dan Aaron Courville, yang juga tersedia online di [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Kerangka kerja **Cloud ML** tertentu, seperti [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), atau [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Pertimbangkan untuk menggunakan jalur pembelajaran [Bangun dan operasikan solusi machine learning dengan Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) dan [Bangun dan Operasikan Solusi Machine Learning dengan Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI Percakapan** dan **Chat Bot**. Ada jalur pembelajaran terpisah [Buat solusi AI percakapan](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), dan Anda juga dapat merujuk ke [posting blog ini](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) untuk detail lebih lanjut.
* **Matematika Mendalam** di balik deep learning. Untuk ini, kami merekomendasikan [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) oleh Ian Goodfellow, Yoshua Bengio, dan Aaron Courville, yang juga tersedia online di [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Untuk pengenalan yang lembut tentang topik _AI di Cloud_, Anda dapat mempertimbangkan untuk mengikuti jalur pembelajaran [Memulai dengan kecerdasan buatan di Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
Untuk pengenalan yang lebih ringan tentang topik _AI di Cloud_, Anda dapat mempertimbangkan untuk mengambil jalur pembelajaran [Memulai dengan kecerdasan buatan di Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Konten
| | Tautan Pelajaran | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Pengaturan Kursus](./lessons/0-course-setup/setup.md) | [Pengaturan Lingkungan Pengembangan Anda](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Pengantar AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Pengantar dan Sejarah AI](./lessons/1-Intro/README.md) | - | - |
| 0 | [Pengaturan Kursus](./lessons/0-course-setup/setup.md) | [Siapkan Lingkungan Pengembangan Anda](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Pengenalan AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Pengenalan dan Sejarah AI](./lessons/1-Intro/README.md) | - | - |
| II | **AI Simbolik** |
| 02 | [Representasi Pengetahuan dan Sistem Pakar](./lessons/2-Symbolic/README.md) | [Sistem Pakar](./lessons/2-Symbolic/Animals.ipynb) / [Ontologi](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Grafik Konsep](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Pengantar Jaringan Neural**](./lessons/3-NeuralNetworks/README.md) |||
| III | [**Pengenalan Jaringan Saraf**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Perceptron Berlapis dan Membuat Kerangka Kerja Sendiri](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Pengantar Framework (PyTorch/TensorFlow) dan Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Computer Vision**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Jelajahi Computer Vision di Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| IV | [**Computer Vision**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Eksplorasi Computer Vision di Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Pengantar Computer Vision. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Convolutional Neural Networks](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Arsitektur CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Jaringan Pra-Latih dan Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) dan [Trik Pelatihan](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 08 | [Jaringan yang Sudah Dilatih dan Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) dan [Trik Pelatihan](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoders dan VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generative Adversarial Networks & Artistic Style Transfer](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Deteksi Objek](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Segmentasi Semantik. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Jelajahi Natural Language Processing di Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Representasi Teks. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embedding Kata Semantik. Word2Vec dan GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Pemodelan Bahasa. Melatih Embedding Anda Sendiri](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Jaringan Rekuren Generatif](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Model Bahasa Besar, Pemrograman Prompt, dan Tugas Few-Shot](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Eksplorasi Natural Language Processing di Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Representasi Teks. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embedding Kata Semantik. Word2Vec dan GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Pemodelan Bahasa. Melatih Embedding Anda Sendiri](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Jaringan Rekurens Generatif](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Model Bahasa Besar, Pemrograman Prompt, dan Tugas Few-Shot](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Teknik AI Lainnya** || |
| 21 | [Algoritma Genetik](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Deep Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -101,68 +101,68 @@ Untuk pengenalan yang lembut tentang topik _AI di Cloud_, Anda dapat mempertimba
| VII | **Etika AI** | | |
| 24 | [Etika AI dan AI yang Bertanggung Jawab](./lessons/7-Ethics/README.md) | [Microsoft Learn: Prinsip AI yang Bertanggung Jawab](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Tambahan** | | |
| 25 | [Jaringan Multi-Modal, CLIP, dan VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 25 | [Jaringan Multi-Modal, CLIP dan VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Setiap Pelajaran Berisi
## Setiap pelajaran mencakup
* Materi pra-baca
* Jupyter Notebook yang dapat dijalankan, sering kali spesifik untuk framework (**PyTorch** atau **TensorFlow**). Notebook ini juga berisi banyak materi teoretis, jadi untuk memahami topik, Anda perlu mempelajari setidaknya satu versi notebook (baik PyTorch atau TensorFlow).
* Materi pra-pembacaan
* Jupyter Notebook yang dapat dijalankan, sering kali spesifik untuk framework (**PyTorch** atau **TensorFlow**). Notebook yang dapat dijalankan juga berisi banyak materi teoretis, jadi untuk memahami topik tersebut, Anda perlu membaca setidaknya satu versi notebook (baik PyTorch atau TensorFlow).
* **Lab** tersedia untuk beberapa topik, yang memberi Anda kesempatan untuk mencoba menerapkan materi yang telah Anda pelajari pada masalah tertentu.
* Beberapa bagian berisi tautan ke modul [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) yang mencakup topik terkait.
## Memulai
- Kami telah membuat [pelajaran pengaturan](./lessons/0-course-setup/setup.md) untuk membantu Anda menyiapkan lingkungan pengembangan Anda. - Untuk Pengajar, kami juga telah membuat [pelajaran pengaturan kurikulum](./lessons/0-course-setup/for-teachers.md)!
- Cara [Menjalankan kode di VSCode atau Codespace](./lessons/0-course-setup/how-to-run.md)
- Kami telah membuat [pelajaran pengaturan](./lessons/0-course-setup/setup.md) untuk membantu Anda mengatur lingkungan pengembangan Anda. - Untuk pendidik, kami juga telah membuat [pelajaran pengaturan kurikulum](./lessons/0-course-setup/for-teachers.md)!
- Cara [Menjalankan kode di VSCode atau Codepace](./lessons/0-course-setup/how-to-run.md)
Ikuti langkah-langkah ini:
Fork Repositori: Klik tombol "Fork" di pojok kanan atas halaman ini.
Fork Repository: Klik tombol "Fork" di sudut kanan atas halaman ini.
Clone Repositori: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Clone Repository: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Jangan lupa untuk memberi bintang (🌟) pada repo ini agar lebih mudah ditemukan nanti.
## Temui Pelajar Lain
Bergabunglah dengan [server Discord AI resmi kami](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) untuk bertemu dan berjejaring dengan pelajar lain yang mengikuti kursus ini dan mendapatkan dukungan.
Bergabunglah dengan [server Discord AI resmi kami](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) untuk bertemu dan berjejaring dengan pelajar lain yang mengikuti kursus ini serta mendapatkan dukungan.
Jika Anda memiliki umpan balik produk atau pertanyaan saat membangun, kunjungi [Forum Pengembang Azure AI Foundry](https://aka.ms/foundry/forum)
## Kuis
> **Catatan tentang kuis**: Semua kuis terdapat dalam folder Quiz-app di etc\quiz-app, atau [Online Di Sini](https://ff-quizzes.netlify.app/). Kuis tersebut terhubung dari dalam pelajaran, aplikasi kuis dapat dijalankan secara lokal atau di-deploy ke Azure; ikuti petunjuk di folder `quiz-app`. Kuis ini secara bertahap sedang dilokalisasi.
> **Catatan tentang kuis**: Semua kuis terdapat di folder Quiz-app dalam etc\quiz-app, atau [Online Di Sini](https://ff-quizzes.netlify.app/). Kuis tersebut terhubung dari dalam pelajaran, aplikasi kuis dapat dijalankan secara lokal atau di-deploy ke Azure; ikuti petunjuk di folder `quiz-app`. Kuis tersebut secara bertahap sedang dilokalisasi.
## Bantuan Dibutuhkan
Apakah Anda memiliki saran atau menemukan kesalahan ejaan atau kode? Ajukan sebuah issue atau buat pull request.
Apakah Anda memiliki saran atau menemukan kesalahan ejaan atau kode? Ajukan masalah atau buat pull request.
## Terima Kasih Khusus
* **✍️ Penulis Utama:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Editor:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustrator Sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Pembuat Kuis:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Kontributor Inti:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ Penulis Utama:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Editor:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustrator Sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Pembuat Kuis:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Kontributor Inti:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Kurikulum Lainnya
Tim kami juga membuat kurikulum lainnya! Lihat:
- [Generative AI untuk Pemula](https://aka.ms/genai-beginners)
- [Generative AI untuk Pemula .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI dengan JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI dengan Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI untuk Pemula](https://aka.ms/ai-beginners)
- [Data Science untuk Pemula](https://aka.ms/datascience-beginners)
- [ML untuk Pemula](https://aka.ms/ml-beginners)
- [Keamanan Siber untuk Pemula](https://github.com/microsoft/Security-101)
- [Pengembangan Web untuk Pemula](https://aka.ms/webdev-beginners)
- [IoT untuk Pemula](https://aka.ms/iot-beginners)
- [Pengembangan XR untuk Pemula](https://github.com/microsoft/xr-development-for-beginners)
- [Menguasai GitHub Copilot untuk Penggunaan Agen](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Menguasai GitHub Copilot untuk Pengembang C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Pilih Petualangan Copilot Anda Sendiri](https://github.com/microsoft/CopilotAdventures)
- [Generative AI untuk Pemula](https://aka.ms/genai-beginners)
- [Generative AI untuk Pemula .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI dengan JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI dengan Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI untuk Pemula](https://aka.ms/ai-beginners)
- [Data Science untuk Pemula](https://aka.ms/datascience-beginners)
- [ML untuk Pemula](https://aka.ms/ml-beginners)
- [Keamanan Siber untuk Pemula](https://github.com/microsoft/Security-101)
- [Pengembangan Web untuk Pemula](https://aka.ms/webdev-beginners)
- [IoT untuk Pemula](https://aka.ms/iot-beginners)
- [Pengembangan XR untuk Pemula](https://github.com/microsoft/xr-development-for-beginners)
- [Menguasai GitHub Copilot untuk Penggunaan Agen](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Menguasai GitHub Copilot untuk Pengembang C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Pilih Petualangan Copilot Anda Sendiri](https://github.com/microsoft/CopilotAdventures)
---
**Penafian**:
Dokumen ini telah diterjemahkan menggunakan layanan penerjemahan AI [Co-op Translator](https://github.com/Azure/co-op-translator). Meskipun kami berupaya untuk memberikan hasil yang akurat, harap diperhatikan bahwa terjemahan otomatis mungkin mengandung kesalahan atau ketidakakuratan. Dokumen asli dalam bahasa aslinya harus dianggap sebagai sumber yang berwenang. Untuk informasi yang bersifat kritis, disarankan menggunakan jasa penerjemahan manusia profesional. Kami tidak bertanggung jawab atas kesalahpahaman atau penafsiran yang keliru yang timbul dari penggunaan terjemahan ini.
Dokumen ini telah diterjemahkan menggunakan layanan penerjemahan AI [Co-op Translator](https://github.com/Azure/co-op-translator). Meskipun kami berusaha untuk memberikan hasil yang akurat, harap diingat bahwa terjemahan otomatis mungkin mengandung kesalahan atau ketidakakuratan. Dokumen asli dalam bahasa aslinya harus dianggap sebagai sumber yang otoritatif. Untuk informasi yang bersifat kritis, disarankan menggunakan jasa penerjemahan manusia profesional. Kami tidak bertanggung jawab atas kesalahpahaman atau penafsiran yang keliru yang timbul dari penggunaan terjemahan ini.

108
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View File

@ -1,8 +1,8 @@
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@ -33,7 +33,7 @@ Esplora il mondo dell'**Intelligenza Artificiale** (AI) con il nostro curriculum
#### Supportato tramite GitHub Action (Automatizzato e Sempre Aggiornato)
[Francese](../fr/README.md) | [Spagnolo](../es/README.md) | [Tedesco](../de/README.md) | [Russo](../ru/README.md) | [Arabo](../ar/README.md) | [Persiano (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Cinese (Semplificato)](../zh/README.md) | [Cinese (Tradizionale, Macao)](../mo/README.md) | [Cinese (Tradizionale, Hong Kong)](../hk/README.md) | [Cinese (Tradizionale, Taiwan)](../tw/README.md) | [Giapponese](../ja/README.md) | [Coreano](../ko/README.md) | [Hindi](../hi/README.md) | [Bengalese](../bn/README.md) | [Marathi](../mr/README.md) | [Nepalese](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portoghese (Portogallo)](../pt/README.md) | [Portoghese (Brasile)](../br/README.md) | [Italiano](./README.md) | [Polacco](../pl/README.md) | [Turco](../tr/README.md) | [Greco](../el/README.md) | [Tailandese](../th/README.md) | [Svedese](../sv/README.md) | [Danese](../da/README.md) | [Norvegese](../no/README.md) | [Finlandese](../fi/README.md) | [Olandese](../nl/README.md) | [Ebraico](../he/README.md) | [Vietnamita](../vi/README.md) | [Indonesiano](../id/README.md) | [Malese](../ms/README.md) | [Tagalog (Filippino)](../tl/README.md) | [Swahili](../sw/README.md) | [Ungherese](../hu/README.md) | [Ceco](../cs/README.md) | [Slovacco](../sk/README.md) | [Rumeno](../ro/README.md) | [Bulgaro](../bg/README.md) | [Serbo (Cirillico)](../sr/README.md) | [Croato](../hr/README.md) | [Sloveno](../sl/README.md) | [Ucraino](../uk/README.md) | [Birmano (Myanmar)](../my/README.md)
[Francese](../fr/README.md) | [Spagnolo](../es/README.md) | [Tedesco](../de/README.md) | [Russo](../ru/README.md) | [Arabo](../ar/README.md) | [Persiano (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Cinese (Semplificato)](../zh/README.md) | [Cinese (Tradizionale, Macao)](../mo/README.md) | [Cinese (Tradizionale, Hong Kong)](../hk/README.md) | [Cinese (Tradizionale, Taiwan)](../tw/README.md) | [Giapponese](../ja/README.md) | [Coreano](../ko/README.md) | [Hindi](../hi/README.md) | [Bengalese](../bn/README.md) | [Marathi](../mr/README.md) | [Nepalese](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portoghese (Portogallo)](../pt/README.md) | [Portoghese (Brasile)](../br/README.md) | [Italiano](./README.md) | [Polacco](../pl/README.md) | [Turco](../tr/README.md) | [Greco](../el/README.md) | [Thailandese](../th/README.md) | [Svedese](../sv/README.md) | [Danese](../da/README.md) | [Norvegese](../no/README.md) | [Finlandese](../fi/README.md) | [Olandese](../nl/README.md) | [Ebraico](../he/README.md) | [Vietnamita](../vi/README.md) | [Indonesiano](../id/README.md) | [Malese](../ms/README.md) | [Tagalog (Filippino)](../tl/README.md) | [Swahili](../sw/README.md) | [Ungherese](../hu/README.md) | [Ceco](../cs/README.md) | [Slovacco](../sk/README.md) | [Rumeno](../ro/README.md) | [Bulgaro](../bg/README.md) | [Serbo (Cirillico)](../sr/README.md) | [Croato](../hr/README.md) | [Sloveno](../sl/README.md) | [Ucraino](../uk/README.md) | [Birmano (Myanmar)](../my/README.md)
**Se desideri supportare ulteriori traduzioni, le lingue disponibili sono elencate [qui](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
@ -44,11 +44,11 @@ Esplora il mondo dell'**Intelligenza Artificiale** (AI) con il nostro curriculum
**[Mappa mentale del corso](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
In questo curriculum imparerai:
In questo curriculum, imparerai:
* I diversi approcci all'Intelligenza Artificiale, incluso il "vecchio e caro" approccio simbolico con **Rappresentazione della Conoscenza** e ragionamento ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Reti Neurali** e **Deep Learning**, che sono al centro dell'AI moderna. Illustreremo i concetti dietro questi argomenti importanti utilizzando codice nei due framework più popolari: [TensorFlow](http://Tensorflow.org) e [PyTorch](http://pytorch.org).
* **Architetture Neurali** per lavorare con immagini e testi. Copriremo modelli recenti, anche se potremmo non essere completamente aggiornati con lo stato dell'arte.
* **Reti Neurali** e **Deep Learning**, che sono al centro dell'AI moderna. Illustreremo i concetti dietro questi argomenti importanti utilizzando codice nei due framework più popolari - [TensorFlow](http://Tensorflow.org) e [PyTorch](http://pytorch.org).
* **Architetture Neurali** per lavorare con immagini e testo. Copriremo modelli recenti, anche se potremmo non essere completamente aggiornati con lo stato dell'arte.
* Approcci meno popolari all'AI, come gli **Algoritmi Genetici** e i **Sistemi Multi-Agente**.
Cosa non copriremo in questo curriculum:
@ -57,9 +57,9 @@ Cosa non copriremo in questo curriculum:
* Casi aziendali sull'uso dell'**AI nel Business**. Considera di seguire il percorso di apprendimento [Introduzione all'AI per utenti aziendali](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) su Microsoft Learn, o [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), sviluppato in collaborazione con [INSEAD](https://www.insead.edu/).
* **Machine Learning Classico**, ben descritto nel nostro [Curriculum di Machine Learning per Principianti](http://github.com/Microsoft/ML-for-Beginners).
* Applicazioni pratiche di AI costruite utilizzando i **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Per questo, ti consigliamo di iniziare con i moduli Microsoft Learn per [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [elaborazione del linguaggio naturale](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI con Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** e altri.
* Specifici **Framework Cloud per il Machine Learning**, come [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), o [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Considera di seguire i percorsi di apprendimento [Costruire e operare soluzioni di machine learning con Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) e [Costruire e operare soluzioni di machine learning con Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI Conversazionale** e **Chat Bot**. Esiste un percorso di apprendimento separato [Creare soluzioni di AI conversazionale](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), e puoi anche fare riferimento a [questo post sul blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) per maggiori dettagli.
* Applicazioni pratiche di AI costruite utilizzando i **[Servizi Cognitivi](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Per questo, ti consigliamo di iniziare con i moduli Microsoft Learn per [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [elaborazione del linguaggio naturale](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[AI Generativa con Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** e altri.
* Specifici **Framework Cloud per il Machine Learning**, come [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), o [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Considera di seguire i percorsi di apprendimento [Crea e gestisci soluzioni di machine learning con Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) e [Crea e gestisci soluzioni di machine learning con Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI Conversazionale** e **Chat Bot**. Esiste un percorso di apprendimento separato [Crea soluzioni di AI conversazionale](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), e puoi anche fare riferimento a [questo post sul blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) per maggiori dettagli.
* **Matematica Avanzata** dietro il deep learning. Per questo, ti consigliamo [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) di Ian Goodfellow, Yoshua Bengio e Aaron Courville, disponibile anche online su [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Per un'introduzione semplice agli argomenti di _AI nel Cloud_, potresti considerare di seguire il percorso di apprendimento [Introduzione all'intelligenza artificiale su Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
@ -68,7 +68,7 @@ Per un'introduzione semplice agli argomenti di _AI nel Cloud_, potresti consider
| | Link alla Lezione | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Configurazione del Corso](./lessons/0-course-setup/setup.md) | [Configura il tuo ambiente di sviluppo](./lessons/0-course-setup/how-to-run.md) | |
| 0 | [Configurazione del Corso](./lessons/0-course-setup/setup.md) | [Configura il tuo Ambiente di Sviluppo](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Introduzione all'AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Introduzione e Storia dell'AI](./lessons/1-Intro/README.md) | - | - |
| II | **AI Simbolica** |
@ -82,21 +82,21 @@ Per un'introduzione semplice agli argomenti di _AI nel Cloud_, potresti consider
| 07 | [Reti Neurali Convoluzionali](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Architetture CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Reti Pre-addestrate e Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) e [Trucchi per l'Addestramento](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoder e VAE](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Reti Generative Avversarie e Trasferimento di Stile Artistico](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Rilevamento Oggetti](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 10 | [Reti Generative Adversariali e Trasferimento di Stile Artistico](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Rilevamento degli Oggetti](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Segmentazione Semantica. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Elaborazione del Linguaggio Naturale**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Esplora l'Elaborazione del Linguaggio Naturale su Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Rappresentazione del Testo. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Word Embeddings Semantici. Word2Vec e GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modellazione del Linguaggio. Addestramento di Embeddings Personalizzati](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Reti Neurali Ricorrenti](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Reti Ricorrenti Generative](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Riconoscimento delle Entità Nominate](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Modelli di Linguaggio di Grandi Dimensioni, Prompt Programming e Few-Shot Tasks](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Rappresentazione del Testo. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embedding Semantici delle Parole. Word2Vec e GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modellazione del Linguaggio. Addestramento dei propri embedding](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Reti Neurali Ricorrenti](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Reti Ricorrenti Generative](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Riconoscimento delle Entità Nominate](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Modelli di Linguaggio di Grandi Dimensioni, Programmazione con Prompt e Task Few-Shot](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Altre Tecniche di AI** || |
| 21 | [Algoritmi Genetici](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Deep Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 22 | [Apprendimento Rinforzato Profondo](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Sistemi Multi-Agente](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Etica dell'AI** | | |
| 24 | [Etica dell'AI e AI Responsabile](./lessons/7-Ethics/README.md) | [Microsoft Learn: Principi di AI Responsabile](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
@ -105,19 +105,19 @@ Per un'introduzione semplice agli argomenti di _AI nel Cloud_, potresti consider
## Ogni lezione contiene
* Materiale di pre-lettura
* Jupyter Notebook eseguibili, spesso specifici per il framework (**PyTorch** o **TensorFlow**). I notebook eseguibili includono anche molto materiale teorico, quindi per comprendere l'argomento è necessario seguire almeno una versione del notebook (PyTorch o TensorFlow).
* Materiale di lettura preliminare
* Jupyter Notebook eseguibili, spesso specifici per il framework (**PyTorch** o **TensorFlow**). Il notebook eseguibile include anche molto materiale teorico, quindi per comprendere l'argomento è necessario seguire almeno una versione del notebook (PyTorch o TensorFlow).
* **Lab** disponibili per alcuni argomenti, che ti danno l'opportunità di applicare il materiale appreso a un problema specifico.
* Alcune sezioni contengono link a moduli di [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) che trattano argomenti correlati.
* Alcune sezioni contengono link ai moduli [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) che trattano argomenti correlati.
## Per iniziare
- Abbiamo creato una [lezione di configurazione](./lessons/0-course-setup/setup.md) per aiutarti a configurare il tuo ambiente di sviluppo. - Per gli educatori, abbiamo creato una [lezione di configurazione del curriculum](./lessons/0-course-setup/for-teachers.md) appositamente per voi!
- Abbiamo creato una [lezione di configurazione](./lessons/0-course-setup/setup.md) per aiutarti a configurare il tuo ambiente di sviluppo. - Per gli educatori, abbiamo creato anche una [lezione di configurazione del curriculum](./lessons/0-course-setup/for-teachers.md)!
- Come [Eseguire il codice in VSCode o Codepace](./lessons/0-course-setup/how-to-run.md)
Segui questi passaggi:
Fork del Repository: Clicca sul pulsante "Fork" in alto a destra di questa pagina.
Fork del Repository: Clicca sul pulsante "Fork" in alto a destra in questa pagina.
Clona il Repository: `git clone https://github.com/microsoft/AI-For-Beginners.git`
@ -125,44 +125,44 @@ Non dimenticare di aggiungere una stella (🌟) a questo repository per trovarlo
## Incontra altri studenti
Unisciti al nostro [server Discord ufficiale di AI](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) per incontrare e fare rete con altri studenti che seguono questo corso e ottenere supporto.
Unisciti al nostro [server Discord ufficiale di AI](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) per incontrare e fare networking con altri studenti che seguono questo corso e ottenere supporto.
Se hai feedback sui prodotti o domande durante la costruzione, visita il nostro [Forum degli Sviluppatori di Azure AI Foundry](https://aka.ms/foundry/forum)
Se hai feedback sul prodotto o domande durante la costruzione, visita il nostro [Forum degli Sviluppatori di Azure AI Foundry](https://aka.ms/foundry/forum)
## Quiz
> **Una nota sui quiz**: Tutti i quiz si trovano nella cartella Quiz-app in etc\quiz-app, oppure [Online Qui](https://ff-quizzes.netlify.app/). Sono collegati all'interno delle lezioni. L'app dei quiz può essere eseguita in locale o distribuita su Azure; segui le istruzioni nella cartella `quiz-app`. La localizzazione è in corso.
## Aiuto Richiesto
> **Una nota sui quiz**: Tutti i quiz si trovano nella cartella Quiz-app in etc\quiz-app, o [Online Qui](https://ff-quizzes.netlify.app/). Sono collegati all'interno delle lezioni. L'app dei quiz può essere eseguita localmente o distribuita su Azure; segui le istruzioni nella cartella `quiz-app`. La localizzazione è in corso.
## Aiuto richiesto
Hai suggerimenti o hai trovato errori di ortografia o di codice? Apri un issue o crea una pull request.
Hai suggerimenti o hai trovato errori di ortografia o di codice? Apri un problema o crea una pull request.
## Ringraziamenti Speciali
## Ringraziamenti speciali
* **✍️ Autore Principale:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Editor:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Illustratrice di Sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Creatrice del Quiz:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Collaboratori Principali:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ Autore principale:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Editor:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Illustratrice di sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Creatrice del quiz:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Collaboratori principali:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Altri Corsi
## Altri curricula
Il nostro team produce altri corsi! Dai un'occhiata a:
Il nostro team produce altri curricula! Dai un'occhiata:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---
**Disclaimer**:
Questo documento è stato tradotto utilizzando il servizio di traduzione automatica [Co-op Translator](https://github.com/Azure/co-op-translator). Sebbene ci impegniamo per garantire l'accuratezza, si prega di notare che le traduzioni automatiche potrebbero contenere errori o imprecisioni. Il documento originale nella sua lingua nativa dovrebbe essere considerato la fonte autorevole. Per informazioni critiche, si consiglia una traduzione professionale eseguita da un traduttore umano. Non siamo responsabili per eventuali fraintendimenti o interpretazioni errate derivanti dall'uso di questa traduzione.
Questo documento è stato tradotto utilizzando il servizio di traduzione automatica [Co-op Translator](https://github.com/Azure/co-op-translator). Sebbene ci impegniamo per garantire l'accuratezza, si prega di notare che le traduzioni automatiche possono contenere errori o imprecisioni. Il documento originale nella sua lingua nativa dovrebbe essere considerato la fonte autorevole. Per informazioni critiche, si raccomanda una traduzione professionale effettuata da un esperto umano. Non siamo responsabili per eventuali incomprensioni o interpretazioni errate derivanti dall'uso di questa traduzione.

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@ -1,8 +1,8 @@
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@ -21,21 +21,21 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# 初心者のための人工知能 - カリキュラム
# 初心者向け人工知能 - カリキュラム
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.ja.png)|
|:---:|
| 初心者のためのAI - _スケッチノート: [@girlie_mac](https://twitter.com/girlie_mac)_ |
| 初心者向けAI - _スケッチノート by [@girlie_mac](https://twitter.com/girlie_mac)_ |
**人工知能**（AI）の世界を、12週間・24レッスンのカリキュラムで探求しましょう！ 実践的なレッスン、クイズ、ラボが含まれています。このカリキュラムは初心者向けで、TensorFlowやPyTorchなどのツール、そしてAI倫理についても扱います。
**人工知能** (AI) の世界を探求する12週間、24レッスンのカリキュラムです！ 実践的なレッスン、クイズ、ラボが含まれています。このカリキュラムは初心者向けで、TensorFlowやPyTorchのようなツール、そしてAIの倫理についても扱います。
### 🌐 多言語対応
#### GitHub Actionによるサポート（自動更新・常に最新）
#### GitHub Actionによるサポート (自動化され、常に最新)
[フランス語](../fr/README.md) | [スペイン語](../es/README.md) | [ドイツ語](../de/README.md) | [ロシア語](../ru/README.md) | [アラビア語](../ar/README.md) | [ペルシャ語（ファルシー）](../fa/README.md) | [ウルドゥー語](../ur/README.md) | [中国語（簡体字）](../zh/README.md) | [中国語（繁体字、マカオ）](../mo/README.md) | [中国語（繁体字、香港）](../hk/README.md) | [中国語（繁体字、台湾）](../tw/README.md) | [日本語](./README.md) | [韓国語](../ko/README.md) | [ヒンディー語](../hi/README.md) | [ベンガル語](../bn/README.md) | [マラーティー語](../mr/README.md) | [ネパール語](../ne/README.md) | [パンジャブ語（グルムキー）](../pa/README.md) | [ポルトガル語（ポルトガル）](../pt/README.md) | [ポルトガル語（ブラジル）](../br/README.md) | [イタリア語](../it/README.md) | [ポーランド語](../pl/README.md) | [トルコ語](../tr/README.md) | [ギリシャ語](../el/README.md) | [タイ語](../th/README.md) | [スウェーデン語](../sv/README.md) | [デンマーク語](../da/README.md) | [ノルウェー語](../no/README.md) | [フィンランド語](../fi/README.md) | [オランダ語](../nl/README.md) | [ヘブライ語](../he/README.md) | [ベトナム語](../vi/README.md) | [インドネシア語](../id/README.md) | [マレー語](../ms/README.md) | [タガログ語（フィリピン語）](../tl/README.md) | [スワヒリ語](../sw/README.md) | [ハンガリー語](../hu/README.md) | [チェコ語](../cs/README.md) | [スロバキア語](../sk/README.md) | [ルーマニア語](../ro/README.md) | [ブルガリア語](../bg/README.md) | [セルビア語（キリル文字）](../sr/README.md) | [クロアチア語](../hr/README.md) | [スロベニア語](../sl/README.md) | [ウクライナ語](../uk/README.md) | [ビルマ語（ミャンマー）](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](./README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**追加の翻訳を希望する場合は、[こちら](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)に記載されている言語をご確認ください。**
**追加の翻訳を希望する場合、サポートされている言語は[こちら](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)に記載されています**
## コミュニティに参加する
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -46,23 +46,23 @@ CO_OP_TRANSLATOR_METADATA:
このカリキュラムでは以下を学びます：
* **人工知能**のさまざまなアプローチ。特に、**知識表現**と推論を用いた「古典的な」シンボリックアプローチ（[GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)）について。
* 現代AIの中核をなす**ニューラルネットワーク**と**ディープラーニング**。これらの重要なトピックの概念を、[TensorFlow](http://Tensorflow.org)や[PyTorch](http://pytorch.org)といった人気のフレームワークを使って説明します。
* 画像やテキストを扱うための**ニューラルアーキテクチャ**。最近のモデルを取り上げますが、最先端の内容には少し欠けるかもしれません。
* **人工知能**のさまざまなアプローチ。特に「古典的な」記号的アプローチである**知識表現**と推論 ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))。
* 現代AIの中心である**ニューラルネットワーク**と**深層学習**。これらの重要なトピックの概念を、人気のあるフレームワークである[TensorFlow](http://Tensorflow.org)と[PyTorch](http://pytorch.org)を使ってコードで説明します。
* 画像やテキストを扱うための**ニューラルアーキテクチャ**。最新のモデルを扱いますが、最先端の内容には少し不足があるかもしれません。
* あまり知られていないAIアプローチ、例えば**遺伝的アルゴリズム**や**マルチエージェントシステム**。
このカリキュラムで扱わない内容：
> [このコースの追加リソースはMicrosoft Learnコレクションでご覧いただけます](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [このコースの追加リソースはMicrosoft Learnコレクションで確認できます](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **ビジネスにおけるAIの活用事例**。Microsoft Learnの[ビジネスユーザー向けAI入門](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum)学習パスや、[INSEAD](https://www.insead.edu/)と共同開発された[AIビジネススクール](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)を受講することをお勧めします。
* **クラシック機械学習**。これは[初心者のための機械学習カリキュラム](http://github.com/Microsoft/ML-for-Beginners)で詳しく説明されています。
* **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**を使用した実践的なAIアプリケーション。これについては、Microsoft Learnの[ビジョン](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然言語処理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[Azure OpenAI Serviceを使った生成AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)**などのモジュールから始めることをお勧めします。
* 特定のML**クラウドフレームワーク**（例：[Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)、[Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)）。[Azure Machine Learningを使った機械学習ソリューションの構築と運用](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum)や[Azure Databricksを使った機械学習ソリューションの構築と運用](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum)学習パスを利用してください。
* **会話型AI**や**チャットボット**。これについては、[会話型AIソリューションの作成](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum)学習パスや、[このブログ記事](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)を参照してください。
* **ディープラーニングの深い数学的背景**。これについては、Ian Goodfellow、Yoshua Bengio、Aaron Courvilleによる[Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)をお勧めします。この本は[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)でもオンラインで利用可能です。
* **AIをビジネスで活用する**事例。Microsoft Learnの[Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum)学習パスや、[AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)を検討してください。これは[INSEAD](https://www.insead.edu/)と共同で開発されました。
* **古典的な機械学習**。これは[Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners)で詳しく説明されています。
* **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**を使用して構築された実践的なAIアプリケーション。これについては、Microsoft Learnの[vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)**などのモジュールから始めることをお勧めします。
* 特定のML **クラウドフレームワーク**、例えば[Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)、または[Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。[Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum)や[Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum)学習パスを検討してください。
* **会話型AI**や**チャットボット**。これには[Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum)学習パスがあり、さらに詳細については[このブログ記事](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)を参照してください。
* 深層学習の**高度な数学**。これについては、Ian Goodfellow、Yoshua Bengio、Aaron Courvilleによる[Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)をお勧めします。この本はオンラインでも利用可能です：[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
クラウドにおけるAIの入門としては、[Azureでの人工知能の入門](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum)学習パスを受講することを検討してください。
クラウドにおける_AIの入門_については、[Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum)学習パスを検討してください。
# コンテンツ
@ -71,29 +71,29 @@ CO_OP_TRANSLATOR_METADATA:
| 0 | [コースセットアップ](./lessons/0-course-setup/setup.md) | [開発環境のセットアップ](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AIの導入**](./lessons/1-Intro/README.md) | | |
| 01 | [AIの導入と歴史](./lessons/1-Intro/README.md) | - | - |
| II | **シンボリックAI** |
| II | **記号的AI** |
| 02 | [知識表現とエキスパートシステム](./lessons/2-Symbolic/README.md) | [エキスパートシステム](./lessons/2-Symbolic/Animals.ipynb) / [オントロジー](./lessons/2-Symbolic/FamilyOntology.ipynb) /[概念グラフ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**ニューラルネットワークの導入**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [パーセプトロン](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [ノートブック](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [ラボ](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [多層パーセプトロンと独自フレームワークの作成](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [ノートブック](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [ラボ](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [フレームワークの紹介 (PyTorch/TensorFlow) と過学習](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**コンピュータビジョン**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azureでコンピュータビジョンを探求](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| IV | [**コンピュータビジョン**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azureでコンピュータビジョンを探る](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [コンピュータビジョンの紹介. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [畳み込みニューラルネットワーク (CNN)](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNNアーキテクチャ](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [事前学習済みネットワークと転移学習](./lessons/4-ComputerVision/08-TransferLearning/README.md) および [トレーニングのコツ](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [オートエンコーダと変分オートエンコーダ (VAEs)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [敵対的生成ネットワーク (GANs) と芸術的スタイル転送](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 07 | [畳み込みニューラルネットワーク](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNNアーキテクチャ](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [事前学習済みネットワークと転移学習](./lessons/4-ComputerVision/08-TransferLearning/README.md) と [トレーニングのコツ](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [オートエンコーダーとVAE](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [敵対的生成ネットワークと芸術的スタイル転送](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [物体検出](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [セマンティックセグメンテーション. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**自然言語処理 (NLP)**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azureで自然言語処理を探求](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [テキスト表現. BoW/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [セマンティック単語埋め込み. Word2VecとGloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [言語モデリング. 独自の埋め込みのトレーニング](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [リカレントニューラルネットワーク (RNN)](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成リカレントネットワーク](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [トランスフォーマー. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [固有表現認識 (NER)](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大規模言語モデル、プロンプトプログラミング、少数ショットタスク](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**自然言語処理**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azureで自然言語処理を探る](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [テキスト表現. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [セマンティック単語埋め込み. Word2VecとGloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [言語モデリング. 独自の埋め込みをトレーニングする](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [リカレントニューラルネットワーク](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成リカレントネットワーク](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [トランスフォーマー. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [固有表現抽出](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大規模言語モデル、プロンプトプログラミングと少数ショットタスク](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **その他のAI技術** || |
| 21 | [遺伝的アルゴリズム](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [深層強化学習](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -106,64 +106,63 @@ CO_OP_TRANSLATOR_METADATA:
## 各レッスンに含まれる内容
* 事前学習資料
* 実行可能なJupyter Notebook（フレームワークに特化したものが多い **PyTorch** または **TensorFlow**）。実行可能なノートブックには多くの理論的な内容も含まれているため、トピックを理解するには少なくとも1つのバージョン（PyTorchまたはTensorFlow）を通して学ぶ必要があります。
* **Lab** が一部のトピックで利用可能で、学んだ内容を特定の問題に適用する機会を提供します。
* 一部のセクションには、関連トピックをカバーする [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) モジュールへのリンクが含まれています。
* 実行可能なJupyter Notebook（主にフレームワークに特化したもの **PyTorch** または **TensorFlow**）。実行可能なノートブックには多くの理論的な内容が含まれているため、トピックを理解するにはPyTorchまたはTensorFlowのいずれかのバージョンを少なくとも一度は通読する必要があります。
* **Lab** がいくつかのトピックで利用可能で、学んだ内容を特定の問題に適用する機会を提供します。
* 一部のセクションには関連トピックをカバーする [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) モジュールへのリンクが含まれています。
## 始め方
- 開発環境のセットアップをサポートするために、[セットアップレッスン](./lessons/0-course-setup/setup.md)を作成しました。
- 教育者向けに、[カリキュラムセットアップレッスン](./lessons/0-course-setup/for-teachers.md)も用意しています！
- 開発環境のセットアップを支援するために [セットアップレッスン](./lessons/0-course-setup/setup.md) を作成しました。 - 教育者向けに [カリキュラムセットアップレッスン](./lessons/0-course-setup/for-teachers.md) も作成しました！
- [VSCodeまたはCodepaceでコードを実行する方法](./lessons/0-course-setup/how-to-run.md)
以下の手順に従ってください：
リポジトリをフォーク: このページの右上にある「Fork」ボタンをクリックします。
リポジトリをフォークする: このページの右上にある「Fork」ボタンをクリックしてください。
リポジトリをクローン: `git clone https://github.com/microsoft/AI-For-Beginners.git`
リポジトリをクローンする: `git clone https://github.com/microsoft/AI-For-Beginners.git`
このリポジトリにスター (🌟) を付けて、後で簡単に見つけられるようにしてください。
このリポジトリを後で簡単に見つけられるようにスター (🌟) を忘れずに付けてください。
## 他の学習者とつながる
## 他の学習者と交流する
[公式AI Discordサーバー](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) に参加して、このコースを受講している他の学習者と交流し、サポートを受けましょう。
プロダクトに関するフィードバックや、構築中の質問がある場合は、[Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) を訪れてください。
構築中に製品フィードバックや質問がある場合は、[Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) を訪問してください。
## クイズ
> **クイズについての注意**: すべてのクイズは、etc\quiz-app内のQuiz-appフォルダーに含まれています。または[オンラインでこちら](https://ff-quizzes.netlify.app/)からアクセスできます。クイズはレッスン内からリンクされています。クイズアプリはローカルで実行することも、Azureにデプロイすることも可能です。`quiz-app`フォルダー内の指示に従ってください。クイズは徐々にローカライズされています。
## ヘルプ募集
提案やスペルミス、コードのエラーを見つけましたか？Issueを立てるか、プルリクエストを作成してください。
提案がありますか？またはスペルミスやコードの誤りを見つけましたか？Issueを立てるか、プルリクエストを作成してください。
## 特別な感謝
* **✍️ 主な著者:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 編集者:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 スケッチノートイラストレーター:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ クイズ作成者:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 コア貢献者:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ 主な著者:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 編集者:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 スケッチノートイラストレーター:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ クイズ作成者:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 コア貢献者:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## その他のカリキュラム
私たちのチームは他にもカリキュラムを制作しています！ぜひチェックしてください：
私たちのチームは他のカリキュラムも制作しています！ぜひチェックしてください：
- [初心者向け生成AI](https://aka.ms/genai-beginners)
- [初心者向け生成AI .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [JavaScriptで学ぶ生成AI](https://github.com/microsoft/generative-ai-with-javascript)
- [Javaで学ぶ生成AI](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [初心者向けAI](https://aka.ms/ai-beginners)
- [初心者向けデータサイエンス](https://aka.ms/datascience-beginners)
- [初心者向け機械学習](https://aka.ms/ml-beginners)
- [初心者向けサイバーセキュリティ](https://github.com/microsoft/Security-101)
- [初心者向けWeb開発](https://aka.ms/webdev-beginners)
- [初心者向けIoT](https://aka.ms/iot-beginners)
- [初心者向けXR開発](https://github.com/microsoft/xr-development-for-beginners)
- [GitHub Copilotを活用したエージェント的利用のマスター](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [C#/.NET開発者向けGitHub Copilotのマスター](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [自分で選ぶCopilotアドベンチャー](https://github.com/microsoft/CopilotAdventures)
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---
**免責事項**:
この文書はAI翻訳サービス[Co-op Translator](https://github.com/Azure/co-op-translator)を使用して翻訳されています。正確性を追求しておりますが、自動翻訳には誤りや不正確な部分が含まれる可能性があります。元の言語で記載された文書を正式な情報源としてご参照ください。重要な情報については、専門の人間による翻訳を推奨します。この翻訳の使用に起因する誤解や誤解釈について、当社は責任を負いません。
この文書は、AI翻訳サービス [Co-op Translator](https://github.com/Azure/co-op-translator) を使用して翻訳されています。正確性を期すよう努めておりますが、自動翻訳には誤りや不正確な表現が含まれる可能性があります。元の言語で記載された原文を公式な情報源としてご参照ください。重要な情報については、専門の人間による翻訳を推奨します。本翻訳の利用に起因する誤解や誤認について、当社は一切の責任を負いません。

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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# 초보자를 위한 인공지능 - 커리큘럼
# 초보자를 위한 인공지능 - 커리큘럼
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.ko.png)|
|:---:|
| 초보자를 위한 AI - _스케치노트: [@girlie_mac](https://twitter.com/girlie_mac)_ |
| 초보자를 위한 인공지능 - _스케치노트: [@girlie_mac](https://twitter.com/girlie_mac)_ |
**인공지능**(AI)의 세계를 12주, 24강으로 구성된 커리큘럼을 통해 탐험해보세요! 실습 강의, 퀴즈, 실험실이 포함되어 있으며, 초보자도 쉽게 따라갈 수 있도록 설계되었습니다. TensorFlow와 PyTorch 같은 도구와 AI 윤리도 다룹니다.
**인공지능**(AI)의 세계를 12주, 24강으로 구성된 커리큘럼을 통해 탐험해보세요! 실습 강의, 퀴즈, 실험실이 포함되어 있으며, 초보자도 쉽게 따라올 수 있도록 설계되었습니다. TensorFlow와 PyTorch 같은 도구와 AI 윤리도 다룹니다.
### 🌐 다국어 지원
### 🌐 다국어 지원
#### GitHub Action을 통한 지원 (자동화 및 항상 최신 상태 유지)
#### GitHub Action을 통한 지원 (자동화 및 항상 최신 상태 유지)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](./README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
@ -40,44 +40,44 @@ CO_OP_TRANSLATOR_METADATA:
## 커뮤니티에 참여하세요
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## 학습 내용
## 학습 내용
**[강의 마인드맵](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[코스 마인드맵](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
이 커리큘럼에서 배우게 될 내용:
* **지식 표현**과 추론을 포함한 "고전적" 상징적 접근법([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))을 포함한 다양한 인공지능 접근법.
* 현대 AI의 핵심인 **신경망**과 **딥러닝**. TensorFlow와 PyTorch라는 두 가지 인기 있는 프레임워크를 사용하여 이 중요한 주제의 개념을 설명합니다.
* 이미지와 텍스트 작업을 위한 **신경망 아키텍처**. 최신 모델을 다루지만 최첨단 기술은 다소 부족할 수 있습니다.
* 현대 AI의 핵심인 **신경망**과 **딥러닝**. 이 중요한 주제의 개념을 TensorFlow와 PyTorch라는 두 가지 인기 있는 프레임워크를 사용하여 설명합니다.
* 이미지와 텍스트 작업을 위한 **신경망 아키텍처**. 최신 모델을 다루지만, 최첨단 기술은 다소 부족할 수 있습니다.
* **유전 알고리즘** 및 **다중 에이전트 시스템**과 같은 덜 알려진 AI 접근법.
이 커리큘럼에서 다루지 않는 내용:
> [이 강의의 추가 자료는 Microsoft Learn 컬렉션에서 확인하세요](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [이 과정의 추가 리소스는 Microsoft Learn 컬렉션에서 확인하세요](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **비즈니스에서의 AI 활용 사례**. Microsoft Learn의 [비즈니스 사용자를 위한 AI 소개](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 학습 경로나 [AI 비즈니스 스쿨](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)을 고려하세요. 이 과정은 [INSEAD](https://www.insead.edu/)와 협력하여 개발되었습니다.
* **고전적 머신러닝**. 이는 [초보자를 위한 머신러닝 커리큘럼](http://github.com/Microsoft/ML-for-Beginners)에서 잘 설명되어 있습니다.
* **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**를 사용하여 구축된 실질적인 AI 응용 프로그램. 이를 위해 Microsoft Learn의 [비전](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [자연어 처리](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI 서비스로 생성형 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 모듈을 시작점으로 삼으세요.
* **클라우드 머신러닝 프레임워크**, 예를 들어 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), 또는 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). [Azure Machine Learning으로 AI 솔루션 구축 및 운영](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 및 [Azure Databricks로 머신러닝 솔루션 구축 및 운영](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 학습 경로를 참고하세요.
* **고전적 머신러닝**, 이는 [초보자를 위한 머신러닝 커리큘럼](http://github.com/Microsoft/ML-for-Beginners)에서 잘 설명되어 있습니다.
* **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**를 사용하여 구축된 실용적인 AI 응용 프로그램. 이를 위해 Microsoft Learn의 [비전](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [자연어 처리](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI 서비스로 생성형 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 등의 모듈을 시작점으로 추천합니다.
* **클라우드 머신러닝 프레임워크**, 예를 들어 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), 또는 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). [Azure Machine Learning으로 AI 솔루션 구축 및 운영](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 및 [Azure Databricks로 머신러닝 솔루션 구축 및 운영](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 학습 경로를 고려하세요.
* **대화형 AI** 및 **챗봇**. 별도의 [대화형 AI 솔루션 만들기](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) 학습 경로가 있으며, [이 블로그 게시물](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)에서 더 자세한 내용을 확인할 수 있습니다.
* 딥러닝의 **심화 수학**. 이를 위해 Ian Goodfellow, Yoshua Bengio, Aaron Courville의 [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)을 추천합니다. 이 책은 [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)에서도 온라인으로 이용할 수 있습니다.
* 딥러닝의 **심화 수학**. 이를 위해 Ian Goodfellow, Yoshua Bengio, Aaron Courville의 [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)을 추천하며, 온라인에서도 확인할 수 있습니다: [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
클라우드에서 _AI_를 부드럽게 시작하려면 [Azure에서 인공지능 시작하기](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 학습 경로를 고려해보세요.
클라우드에서 _AI_를 다루는 주제에 대한 간단한 소개를 원하시면 [Azure에서 인공지능 시작하기](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 학습 경로를 고려하세요.
# 콘텐츠
# 콘텐츠
| | 강의 링크 | PyTorch/Keras/TensorFlow | 실습 |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [강의 준비](./lessons/0-course-setup/setup.md) | [개발 환경 설정](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI 소개**](./lessons/1-Intro/README.md) | | |
| 01 | [AI 소개 및 역사](./lessons/1-Intro/README.md) | - | - |
| II | **상징적 AI** |
| 02 | [지식 표현 및 전문가 시스템](./lessons/2-Symbolic/README.md) | [전문가 시스템](./lessons/2-Symbolic/Animals.ipynb) / [온톨로지](./lessons/2-Symbolic/FamilyOntology.ipynb) /[개념 그래프](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**신경망 소개**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [퍼셉트론](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [노트북](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [실습](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| | 강의 링크 | PyTorch/Keras/TensorFlow | 실습 |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [코스 설정](./lessons/0-course-setup/setup.md) | [개발 환경 설정](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI 소개**](./lessons/1-Intro/README.md) | | |
| 01 | [AI 소개 및 역사](./lessons/1-Intro/README.md) | - | - |
| II | **상징적 AI** |
| 02 | [지식 표현 및 전문가 시스템](./lessons/2-Symbolic/README.md) | [전문가 시스템](./lessons/2-Symbolic/Animals.ipynb) / [온톨로지](./lessons/2-Symbolic/FamilyOntology.ipynb) /[개념 그래프](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**신경망 소개**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [퍼셉트론](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [노트북](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [실습](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [다층 퍼셉트론 및 자체 프레임워크 생성](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [노트북](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [실습](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [프레임워크 소개 (PyTorch/TensorFlow) 및 과적합](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [실습](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**컴퓨터 비전**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure에서 컴퓨터 비전 탐구하기](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| IV | [**컴퓨터 비전**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure에서 컴퓨터 비전 탐색](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [컴퓨터 비전 소개. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [노트북](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [실습](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [합성곱 신경망](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN 아키텍처](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [실습](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [사전 학습된 네트워크 및 전이 학습](./lessons/4-ComputerVision/08-TransferLearning/README.md) 및 [훈련 팁](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [실습](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
@ -85,51 +85,52 @@ CO_OP_TRANSLATOR_METADATA:
| 10 | [생성적 적대 신경망 및 예술적 스타일 전이](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [객체 탐지](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [실습](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [의미론적 분할. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**자연어 처리**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure에서 자연어 처리 탐구하기](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [텍스트 표현. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [의미론적 단어 임베딩. Word2Vec 및 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [언어 모델링. 임베딩 직접 훈련하기](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [실습](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [순환 신경망](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [생성적 순환 네트워크](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [실습](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [트랜스포머. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [개체명 인식](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [실습](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [대규모 언어 모델, 프롬프트 프로그래밍 및 Few-Shot 작업](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**자연어 처리**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure에서 자연어 처리 탐색](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [텍스트 표현. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [의미론적 단어 임베딩. Word2Vec 및 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [언어 모델링. 임베딩 직접 훈련하기](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [실습](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [순환 신경망](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [생성적 순환 네트워크](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [실습](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [트랜스포머. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [개체명 인식](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [실습](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [대형 언어 모델, 프롬프트 프로그래밍 및 Few-Shot 작업](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **기타 AI 기술** || |
| 21 | [유전 알고리즘](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [노트북](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [심층 강화 학습](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [실습](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [다중 에이전트 시스템](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI 윤리** | | |
| 24 | [AI 윤리 및 책임 있는 AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: 책임 있는 AI 원칙](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **기타** | | |
| IX | **추가 자료** | | |
| 25 | [멀티모달 네트워크, CLIP 및 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [노트북](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## 각 강의에는 다음이 포함됩니다
## 각 강의는 다음을 포함합니다
* 사전 읽기 자료
* 실행 가능한 Jupyter 노트북. 이는 주로 프레임워크(**PyTorch** 또는 **TensorFlow**)에 따라 다릅니다. 실행 가능한 노트북에는 많은 이론적 자료도 포함되어 있으므로, 주제를 이해하려면 노트북 버전 중 하나(Pytorch 또는 TensorFlow)를 반드시 학습해야 합니다.
* 사전 학습 자료
* 실행 가능한 Jupyter 노트북, 주로 프레임워크(**PyTorch** 또는 **TensorFlow**)에 따라 제공됩니다. 실행 가능한 노트북에는 많은 이론적 내용이 포함되어 있으므로 주제를 이해하려면 노트북 버전 중 하나(Pytorch 또는 TensorFlow)를 반드시 학습해야 합니다.
* **실습**은 일부 주제에서 제공되며, 학습한 내용을 특정 문제에 적용해볼 기회를 제공합니다.
* 일부 섹션에는 관련 주제를 다루는 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 모듈 링크가 포함되어 있습니다.
## 시작하기
- 개발 환경 설정을 돕기 위해 [설정 강의](./lessons/0-course-setup/setup.md)를 준비했습니다.
- 교육자를 위해 [커리큘럼 설정 강의](./lessons/0-course-setup/for-teachers.md)도 준비했습니다!
- 개발 환경 설정을 돕기 위해 [설정 강의](./lessons/0-course-setup/setup.md)를 준비했습니다. - 교육자를 위해 [교사용 커리큘럼 설정 강의](./lessons/0-course-setup/for-teachers.md)도 준비했습니다!
- [VSCode 또는 Codepace에서 코드 실행 방법](./lessons/0-course-setup/how-to-run.md)
다음 단계를 따르세요:
1. 리포지토리 포크: 이 페이지 오른쪽 상단의 "Fork" 버튼을 클릭하세요.
2. 리포지토리 클론: `git clone https://github.com/microsoft/AI-For-Beginners.git`
3. 이 리포지토리를 별표(🌟) 표시하여 나중에 쉽게 찾을 수 있도록 하세요.
저장소 포크: 이 페이지 오른쪽 상단의 "Fork" 버튼을 클릭하세요.
저장소 클론: `git clone https://github.com/microsoft/AI-For-Beginners.git`
이 저장소를 나중에 쉽게 찾을 수 있도록 별표(🌟)를 잊지 마세요.
## 다른 학습자 만나기
[공식 AI Discord 서버](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)에 참여하여 이 과정을 수강하는 다른 학습자들과 네트워크를 형성하고 지원을 받으세요.
[공식 AI Discord 서버](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)에 가입하여 이 과정을 수강하는 다른 학습자들과 네트워크를 형성하고 지원을 받으세요.
제품 피드백이나 질문이 있다면 [Azure AI Foundry 개발자 포럼](https://aka.ms/foundry/forum)을 방문하세요.
제품 피드백이나 질문이 있을 경우 [Azure AI Foundry 개발자 포럼](https://aka.ms/foundry/forum)을 방문하세요.
## 퀴즈
> **퀴즈에 대한 참고 사항**: 모든 퀴즈는 etc\quiz-app의 Quiz-app 폴더에 포함되어 있으며, [온라인에서 확인하기](https://ff-quizzes.netlify.app/)도 가능합니다. 퀴즈는 각 수업 내에서 연결되어 있으며, 로컬에서 실행하거나 Azure에 배포할 수 있습니다. `quiz-app` 폴더의 지침을 따라주세요. 퀴즈는 점진적으로 현지화되고 있습니다.
> **퀴즈에 대한 참고 사항**: 모든 퀴즈는 etc\quiz-app 폴더의 Quiz-app 폴더에 포함되어 있으며, [온라인 링크](https://ff-quizzes.netlify.app/)에서도 확인할 수 있습니다. 퀴즈는 각 레슨 내에서 연결되어 있으며, 로컬에서 실행하거나 Azure에 배포할 수 있습니다. `quiz-app` 폴더의 지침을 따라주세요. 퀴즈는 점차적으로 현지화되고 있습니다.
## 도움 요청
제안 사항이 있거나 철자 또는 코드 오류를 발견하셨나요? 이슈를 제기하거나 풀 리퀘스트를 생성해 주세요.
@ -144,12 +145,12 @@ CO_OP_TRANSLATOR_METADATA:
## 기타 커리큘럼
우리 팀은 다른 커리큘럼도 제작합니다! 확인해 보세요:
저희 팀은 다른 커리큘럼도 제작합니다! 아래를 확인해 보세요:
- [초보자를 위한 생성형 AI](https://aka.ms/genai-beginners)
- [초보자를 위한 생성형 AI .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [JavaScript로 생성형 AI](https://github.com/microsoft/generative-ai-with-javascript)
- [Java로 생성형 AI](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [JavaScript로 배우는 생성형 AI](https://github.com/microsoft/generative-ai-with-javascript)
- [Java로 배우는 생성형 AI](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [초보자를 위한 AI](https://aka.ms/ai-beginners)
- [초보자를 위한 데이터 과학](https://aka.ms/datascience-beginners)
- [초보자를 위한 머신러닝](https://aka.ms/ml-beginners)
@ -164,4 +165,4 @@ CO_OP_TRANSLATOR_METADATA:
---
**면책 조항**:
이 문서는 AI 번역 서비스 [Co-op Translator](https://github.com/Azure/co-op-translator)를 사용하여 번역되었습니다. 정확성을 위해 최선을 다하고 있지만, 자동 번역에는 오류나 부정확성이 포함될 수 있습니다. 원본 문서의 원어 버전이 권위 있는 출처로 간주되어야 합니다. 중요한 정보의 경우, 전문적인 인간 번역을 권장합니다. 이 번역 사용으로 인해 발생하는 오해나 잘못된 해석에 대해 책임을 지지 않습니다.
이 문서는 AI 번역 서비스 [Co-op Translator](https://github.com/Azure/co-op-translator)를 사용하여 번역되었습니다. 정확성을 위해 최선을 다하고 있으나, 자동 번역에는 오류나 부정확성이 포함될 수 있습니다. 원본 문서를 해당 언어로 작성된 상태에서 권위 있는 자료로 간주해야 합니다. 중요한 정보의 경우, 전문적인 인간 번역을 권장합니다. 이 번역 사용으로 인해 발생할 수 있는 오해나 잘못된 해석에 대해 당사는 책임을 지지 않습니다.

116
translations/lt/README.md
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@ -1,8 +1,8 @@
<!--
CO_OP_TRANSLATOR_METADATA:
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"translation_date": "2025-09-07T14:17:40+00:00",
"source_file": "README.md",
"language_code": "lt"
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@ -21,19 +21,19 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Dirbtinis intelektas pradedantiesiems – mokymo programa
# Dirbtinis intelektas pradedantiesiems - mokymo programa
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.lt.png)|
|:---:|
| Dirbtinis intelektas pradedantiesiems - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ |
Atraskite **dirbtinio intelekto** (DI) pasaulį su mūsų 12 savaičių, 24 pamokų mokymo programa! Ji apima praktines pamokas, testus ir laboratorijas. Mokymo programa yra pritaikyta pradedantiesiems ir apima tokias priemones kaip TensorFlow ir PyTorch, taip pat DI etiką.
Atraskite **dirbtinio intelekto** (DI) pasaulį su mūsų 12 savaičių, 24 pamokų mokymo programa! Ji apima praktines pamokas, testus ir laboratorijas. Mokymo programa yra pritaikyta pradedantiesiems ir apima tokias priemones kaip TensorFlow ir PyTorch, taip pat DI etikos temas.
### 🌐 Daugiakalbė parama
### 🌐 Daugiakalbė palaikymas
#### Palaikoma per GitHub Action (automatiškai ir visada atnaujinama)
#### Palaikoma per GitHub Action (automatiškai ir visada atnaujinta)
[Prancūzų](../fr/README.md) | [Ispanų](../es/README.md) | [Vokiečių](../de/README.md) | [Rusų](../ru/README.md) | [Arabų](../ar/README.md) | [Persų (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Kinų (supaprastinta)](../zh/README.md) | [Kinų (tradicinė, Makao)](../mo/README.md) | [Kinų (tradicinė, Honkongas)](../hk/README.md) | [Kinų (tradicinė, Taivanas)](../tw/README.md) | [Japonų](../ja/README.md) | [Korėjiečių](../ko/README.md) | [Hindi](../hi/README.md) | [Bengalų](../bn/README.md) | [Maratų](../mr/README.md) | [Nepalų](../ne/README.md) | [Pandžabų (Gurmukhi)](../pa/README.md) | [Portugalų (Portugalija)](../pt/README.md) | [Portugalų (Brazilija)](../br/README.md) | [Italų](../it/README.md) | [Lenkų](../pl/README.md) | [Turkų](../tr/README.md) | [Graikų](../el/README.md) | [Tajų](../th/README.md) | [Švedų](../sv/README.md) | [Danų](../da/README.md) | [Norvegų](../no/README.md) | [Suomių](../fi/README.md) | [Olandų](../nl/README.md) | [Hebrajų](../he/README.md) | [Vietnamiečių](../vi/README.md) | [Indoneziečių](../id/README.md) | [Malajų](../ms/README.md) | [Tagalogų (Filipinų)](../tl/README.md) | [Svahilių](../sw/README.md) | [Vengrų](../hu/README.md) | [Čekų](../cs/README.md) | [Slovakų](../sk/README.md) | [Rumunų](../ro/README.md) | [Bulgarų](../bg/README.md) | [Serbų (kirilica)](../sr/README.md) | [Kroatų](../hr/README.md) | [Slovėnų](../sl/README.md) | [Ukrainiečių](../uk/README.md) | [Birmos (Mianmaras)](../my/README.md)
[Prancūzų](../fr/README.md) | [Ispanų](../es/README.md) | [Vokiečių](../de/README.md) | [Rusų](../ru/README.md) | [Arabų](../ar/README.md) | [Persų (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Kinų (supaprastinta)](../zh/README.md) | [Kinų (tradicinė, Makao)](../mo/README.md) | [Kinų (tradicinė, Honkongas)](../hk/README.md) | [Kinų (tradicinė, Taivanas)](../tw/README.md) | [Japonų](../ja/README.md) | [Korėjiečių](../ko/README.md) | [Hindi](../hi/README.md) | [Bengalų](../bn/README.md) | [Marathi](../mr/README.md) | [Nepalų](../ne/README.md) | [Pundžabi (Gurmukhi)](../pa/README.md) | [Portugalų (Portugalija)](../pt/README.md) | [Portugalų (Brazilija)](../br/README.md) | [Italų](../it/README.md) | [Lenkų](../pl/README.md) | [Turkų](../tr/README.md) | [Graikų](../el/README.md) | [Tajų](../th/README.md) | [Švedų](../sv/README.md) | [Danų](../da/README.md) | [Norvegų](../no/README.md) | [Suomių](../fi/README.md) | [Olandų](../nl/README.md) | [Hebrajų](../he/README.md) | [Vietnamiečių](../vi/README.md) | [Indoneziečių](../id/README.md) | [Malajų](../ms/README.md) | [Tagalog (Filipiniečių)](../tl/README.md) | [Svahilių](../sw/README.md) | [Vengrų](../hu/README.md) | [Čekų](../cs/README.md) | [Slovakų](../sk/README.md) | [Rumunų](../ro/README.md) | [Bulgarų](../bg/README.md) | [Serbų (kirilica)](../sr/README.md) | [Kroatų](../hr/README.md) | [Slovėnų](../sl/README.md) | [Ukrainiečių](../uk/README.md) | [Birmos (Mianmaras)](../my/README.md)
**Jei norite pridėti papildomų vertimų, palaikomos kalbos yra išvardytos [čia](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
@ -46,23 +46,23 @@ Atraskite **dirbtinio intelekto** (DI) pasaulį su mūsų 12 savaičių, 24 pamo
Šioje mokymo programoje išmoksite:
* Skirtingų dirbtinio intelekto metodų, įskaitant „gerąjį senąjį“ simbolinį metodą su **žinių reprezentacija** ir samprotavimu ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neuroninius tinklus** ir **gilųjį mokymąsi**, kurie yra šiuolaikinio DI pagrindas. Šias svarbias temas iliustruosime kodu, naudodami du populiariausius karkasus - [TensorFlow](http://Tensorflow.org) ir [PyTorch](http://pytorch.org).
* **Neuronines architektūras**, skirtas darbui su vaizdais ir tekstu. Nagrinėsime naujausius modelius, tačiau gali trūkti pačių pažangiausių.
* Mažiau populiarius DI metodus, tokius kaip **genetiniai algoritmai** ir **daugiaveiksmės sistemos**.
* Skirtingus dirbtinio intelekto metodus, įskaitant „seną gerą“ simbolinį metodą su **žinių reprezentacija** ir samprotavimu ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neuroninius tinklus** ir **gilųjį mokymąsi**, kurie yra šiuolaikinio DI pagrindas. Šių svarbių temų koncepcijas iliustruosime kodu, naudodami du populiariausius karkasus - [TensorFlow](http://Tensorflow.org) ir [PyTorch](http://pytorch.org).
* **Neuronines architektūras**, skirtas darbui su vaizdais ir tekstu. Aptarsime naujausius modelius, tačiau gali būti, kad šiek tiek trūks pažangiausių technologijų.
* Mažiau populiarius DI metodus, tokius kaip **genetinius algoritmus** ir **daugiaveiksnius sistemas**.
Ko neapimsime šioje mokymo programoje:
Ko neaptarsime šioje mokymo programoje:
> [Visus papildomus šio kurso išteklius rasite mūsų Microsoft Learn kolekcijoje](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **DI versle** naudojimo atvejų. Rekomenduojame mokymosi kelią [Įvadas į DI verslo vartotojams](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) arba [DI verslo mokyklą](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), sukurtą bendradarbiaujant su [INSEAD](https://www.insead.edu/).
* **Klasikinio mašininio mokymosi**, kuris puikiai aprašytas mūsų [Mašininio mokymosi pradedantiesiems mokymo programoje](http://github.com/Microsoft/ML-for-Beginners).
* Praktinių DI programų, sukurtų naudojant **[Kognityvines paslaugas](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Rekomenduojame pradėti nuo Microsoft Learn modulių, skirtų [vaizdams](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natūralios kalbos apdorojimui](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generatyviniam DI su Azure OpenAI paslauga](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** ir kitiems.
* Specifinių ML **debesų karkasų**, tokių kaip [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) ar [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Rekomenduojame mokymosi kelius [Kurti ir valdyti mašininio mokymosi sprendimus su Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) ir [Kurti ir valdyti mašininio mokymosi sprendimus su Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Pokalbių DI** ir **pokalbių robotus**. Yra atskiras mokymosi kelias [Kurti pokalbių DI sprendimus](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), taip pat galite pasinaudoti [šiuo tinklaraščio įrašu](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) norėdami sužinoti daugiau.
* **Giliąją matematiką**, susijusią su giliuoju mokymusi. Rekomenduojame Ian Goodfellow, Yoshua Bengio ir Aaron Courville knygą [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618), kuri taip pat prieinama internete [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* **DI versle** verslo atvejų. Rekomenduojame išklausyti [Įvadas į DI verslo vartotojams](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) mokymosi kelią Microsoft Learn arba [DI verslo mokyklą](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), sukurtą bendradarbiaujant su [INSEAD](https://www.insead.edu/).
* **Klasikinį mašininį mokymąsi**, kuris gerai aprašytas mūsų [Mašininio mokymosi pradedantiesiems mokymo programoje](http://github.com/Microsoft/ML-for-Beginners).
* Praktines DI programas, sukurtas naudojant **[Kognityvines paslaugas](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Rekomenduojame pradėti nuo Microsoft Learn modulių, skirtų [vaizdams](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natūralios kalbos apdorojimui](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generatyviniam DI su Azure OpenAI paslauga](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** ir kitiems.
* Specifinius ML **debesų karkasus**, tokius kaip [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) arba [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Rekomenduojame naudoti [Kurti ir valdyti mašininio mokymosi sprendimus su Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) ir [Kurti ir valdyti mašininio mokymosi sprendimus su Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) mokymosi kelius.
* **Pokalbių DI** ir **pokalbių robotus**. Yra atskiras [Kurti pokalbių DI sprendimus](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) mokymosi kelias, taip pat galite pasinaudoti [šiuo tinklaraščio įrašu](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) norėdami sužinoti daugiau.
* **Giliąją matematiką**, susijusią su giliuoju mokymusi. Tam rekomenduojame [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) Ian Goodfellow, Yoshua Bengio ir Aaron Courville, kuri taip pat prieinama internete [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Norėdami švelniai pradėti su _DI debesyje_, galite pasirinkti mokymosi kelią [Pradėti dirbtinio intelekto naudojimą Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
Norėdami švelniai pradėti _DI debesyje_ temas, galite apsvarstyti galimybę išklausyti [Pradėti dirbtinio intelekto mokymąsi Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) mokymosi kelią.
# Turinys
@ -72,65 +72,65 @@ Norėdami švelniai pradėti su _DI debesyje_, galite pasirinkti mokymosi kelią
| I | [**Įvadas į DI**](./lessons/1-Intro/README.md) | | |
| 01 | [Įvadas ir DI istorija](./lessons/1-Intro/README.md) | - | - |
| II | **Simbolinis DI** |
| 02 | [Žinių reprezentacija ir ekspertų sistemos](./lessons/2-Symbolic/README.md) | [Ekspertų sistemos](./lessons/2-Symbolic/Animals.ipynb) / [Ontologija](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Koncepcijų grafas](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| 02 | [Žinių reprezentacija ir ekspertų sistemos](./lessons/2-Symbolic/README.md) | [Ekspertų sistemos](./lessons/2-Symbolic/Animals.ipynb) / [Ontologija](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Konceptų grafas](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Įvadas į neuroninius tinklus**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptronas](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Užrašų knygelė](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Laboratorija](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Daugiasluoksnis perceptronas ir savo karkaso kūrimas](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Užrašų knygelė](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Laboratorija](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Įvadas į karkasus (PyTorch/TensorFlow) ir permokymą](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorija](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Kompiuterinė rega**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Tyrinėkite kompiuterinę regą „Microsoft Azure“](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Įvadas į kompiuterinę regą. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Užrašinė](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Laboratorija](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvoliuciniai neuroniniai tinklai](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN architektūros](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Laboratorija](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Iš anksto apmokyti tinklai ir perkėlimo mokymasis](./lessons/4-ComputerVision/08-TransferLearning/README.md) ir [Mokymo gudrybės](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorija](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 05 | [Įvadas į Frameworks (PyTorch/TensorFlow) ir Perteklinį Mokymąsi](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorija](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Kompiuterinė Vizija**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Tyrinėkite Kompiuterinę Viziją Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Įvadas į Kompiuterinę Viziją. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Užrašų knygelė](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Laboratorija](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvoliuciniai Neuroniniai Tinklai](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN Architektūros](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Laboratorija](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Iš anksto apmokyti tinklai ir Perkėlimo Mokymasis](./lessons/4-ComputerVision/08-TransferLearning/README.md) ir [Mokymo Triukai](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorija](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoenkoderiai ir VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generatyviniai priešiniai tinklai ir meninio stiliaus perkėlimas](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Objektų atpažinimas](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Laboratorija](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantinis segmentavimas. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Natūralios kalbos apdorojimas**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Tyrinėkite natūralios kalbos apdorojimą „Microsoft Azure“](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Teksto reprezentacija. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantiniai žodžių įterpimai. Word2Vec ir GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Kalbos modeliavimas. Mokykitės savo įterpimų](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratorija](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Pasikartojantys neuroniniai tinklai](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatyviniai pasikartojantys tinklai](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Laboratorija](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformeriai. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Pavadintų objektų atpažinimas](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratorija](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Dideli kalbos modeliai, užklausų programavimas ir mažų pavyzdžių užduotys](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Kitos AI technikos** || |
| 21 | [Genetiniai algoritmai](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Užrašinė](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Gilus pastiprinimo mokymasis](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Laboratorija](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Daugiaveiksmės sistemos](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI etika** | | |
| 24 | [AI etika ir atsakingas AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Atsakingo AI principai](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Papildoma medžiaga** | | |
| 25 | [Daugiarūšiai tinklai, CLIP ir VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Užrašinė](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 10 | [Generatyviniai Priešiški Tinklai ir Meninio Stiliaus Perkėlimas](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Objektų Atpažinimas](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Laboratorija](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantinis Segmentavimas. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Natūralios Kalbos Apdorojimas**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Tyrinėkite Natūralios Kalbos Apdorojimą Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Teksto Atvaizdavimas. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantiniai Žodžių Įterpimai. Word2Vec ir GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Kalbos Modeliavimas. Mokymasis Kurti Savo Įterpimus](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratorija](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Pasikartojantys Neuroniniai Tinklai](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatyviniai Pasikartojantys Tinklai](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Laboratorija](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformatoriai. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Pavadintų Entitetų Atpažinimas](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratorija](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Dideli Kalbos Modeliai, Užklausų Programavimas ir Mažai Pavyzdžių Turinčios Užduotys](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Kiti AI Metodai** || |
| 21 | [Genetiniai Algoritmai](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Užrašų knygelė](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Gilus Stiprinamasis Mokymasis](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Laboratorija](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Daugelio Agentų Sistemos](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI Etika** | | |
| 24 | [AI Etika ir Atsakingas AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Atsakingo AI Principai](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Papildoma** | | |
| 25 | [Daugiarūšiai Tinklai, CLIP ir VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Užrašų knygelė](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Kiekviena pamoka apima
* Priešmokyklinę medžiagą
* Vykdomas Jupyter užrašines, kurios dažnai yra pritaikytos konkrečiam karkasui (**PyTorch** arba **TensorFlow**). Vykdomoje užrašinėje taip pat yra daug teorinės medžiagos, todėl norint suprasti temą, reikia peržiūrėti bent vieną užrašinės versiją (arba PyTorch, arba TensorFlow).
* Medžiagą prieš skaitymą
* Vykdomas Jupyter užrašų knygeles, kurios dažnai yra pritaikytos konkrečiam framework'ui (**PyTorch** arba **TensorFlow**). Vykdomoje užrašų knygelėje taip pat yra daug teorinės medžiagos, todėl norint suprasti temą, reikia peržiūrėti bent vieną užrašų knygelės versiją (arba PyTorch, arba TensorFlow).
* **Laboratorijas**, kurios yra prieinamos kai kurioms temoms ir suteikia galimybę pritaikyti išmoktą medžiagą konkrečiai problemai.
* Kai kuriuose skyriuose yra nuorodos į [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) modulius, kurie apima susijusias temas.
## Pradžia
- Mes sukūrėme [paruošimo pamoką](./lessons/0-course-setup/setup.md), kuri padės jums nustatyti savo kūrimo aplinką. - Mokytojams sukūrėme [mokymo programos paruošimo pamoką](./lessons/0-course-setup/for-teachers.md)!
- Kaip [paleisti kodą VSCode arba Codepace](./lessons/0-course-setup/how-to-run.md)
- Mes sukūrėme [paruošimo pamoką](./lessons/0-course-setup/setup.md), kad padėtume jums pasiruošti savo vystymo aplinką. - Mokytojams mes taip pat sukūrėme [mokymo programos paruošimo pamoką](./lessons/0-course-setup/for-teachers.md)!
- Kaip [Paleisti kodą VSCode arba Codepace](./lessons/0-course-setup/how-to-run.md)
Atlikite šiuos veiksmus:
Sekite šiuos žingsnius:
Fork'uokite saugyklą: Spustelėkite mygtuką „Fork“ šio puslapio viršutiniame dešiniajame kampe.
Fork'uokite saugyklą: Paspauskite "Fork" mygtuką viršutiniame dešiniajame šios puslapio kampe.
Klonuokite saugyklą: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Nepamirškite pažymėti žvaigždute (🌟) šios saugyklos, kad vėliau ją lengviau rastumėte.
Nepamirškite pažymėti (🌟) šios saugyklos, kad vėliau ją būtų lengviau rasti.
## Susipažinkite su kitais besimokančiaisiais
## Susipažinkite su kitais mokiniais
Prisijunkite prie mūsų [oficialaus AI Discord serverio](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), kad susipažintumėte ir bendrautumėte su kitais šio kurso dalyviais bei gautumėte pagalbą.
Prisijunkite prie mūsų [oficialaus AI Discord serverio](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), kad susipažintumėte ir bendrautumėte su kitais mokiniais, kurie mokosi šio kurso, ir gautumėte pagalbą.
Jei turite atsiliepimų apie produktą ar klausimų, susijusių su kūrimu, apsilankykite mūsų [Azure AI Foundry kūrėjų forume](https://aka.ms/foundry/forum)
Jei turite produktų atsiliepimų ar klausimų, kol kuriate, apsilankykite mūsų [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Viktorinos
> **Pastaba apie viktorinas**: Visos viktorinos yra saugomos aplanke Quiz-app, esančiame etc\quiz-app, arba [Internete čia](https://ff-quizzes.netlify.app/). Jos yra susietos su pamokomis, o viktorinų programėlę galima paleisti vietoje arba įdiegti į Azure; sekite instrukcijas aplanke `quiz-app`. Jos palaipsniui yra lokalizuojamos.
## Testai
> **Pastaba apie viktorinas**: Visos viktorinos yra saugomos aplanke Quiz-app, esančiame etc\quiz-app, arba [Internete čia](https://ff-quizzes.netlify.app/). Jos yra susietos su pamokomis, o viktorinų programėlė gali būti paleista lokaliai arba įdiegta į Azure; sekite instrukcijas aplanke `quiz-app`. Jos palaipsniui yra lokalizuojamos.
## Reikalinga pagalba
Turite pasiūlymų ar radote rašybos ar kodo klaidų? Sukurkite problemą arba pateikite „pull request“.
@ -165,4 +165,4 @@ Mūsų komanda kuria ir kitus mokymo kursus! Peržiūrėkite:
---
**Atsakomybės apribojimas**:
Šis dokumentas buvo išverstas naudojant AI vertimo paslaugą [Co-op Translator](https://github.com/Azure/co-op-translator). Nors siekiame tikslumo, prašome atkreipti dėmesį, kad automatiniai vertimai gali turėti klaidų ar netikslumų. Originalus dokumentas jo gimtąja kalba turėtų būti laikomas autoritetingu šaltiniu. Kritinei informacijai rekomenduojama naudoti profesionalų žmogaus vertimą. Mes neprisiimame atsakomybės už nesusipratimus ar klaidingus interpretavimus, atsiradusius dėl šio vertimo naudojimo.
Šis dokumentas buvo išverstas naudojant AI vertimo paslaugą [Co-op Translator](https://github.com/Azure/co-op-translator). Nors siekiame tikslumo, prašome atkreipti dėmesį, kad automatiniai vertimai gali turėti klaidų ar netikslumų. Originalus dokumentas jo gimtąja kalba turėtų būti laikomas autoritetingu šaltiniu. Kritinei informacijai rekomenduojama profesionali žmogaus vertimo paslauga. Mes neprisiimame atsakomybės už nesusipratimus ar klaidingus interpretavimus, atsiradusius naudojant šį vertimą.

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translations/mo/README.md
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@ -1,8 +1,8 @@
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@ -27,15 +27,15 @@ CO_OP_TRANSLATOR_METADATA:
|:---:|
| 人工智慧入門課程 - _由 [@girlie_mac](https://twitter.com/girlie_mac) 繪製的手繪筆記_ |
探索 **人工智慧** (AI) 的世界，透過我們為期 12 週、共 24 節課的課程！課程包含實作教學、測驗以及實驗室練習。此課程適合初學者，涵蓋 TensorFlow 和 PyTorch 等工具，以及人工智慧的倫理議題。
探索 **人工智慧** (AI) 的世界，透過我們為期 12 週、共 24 節課的課程！課程包含實作教學、測驗及實驗室練習。此課程適合初學者，涵蓋 TensorFlow 和 PyTorch 等工具，以及人工智慧的倫理議題。
### 🌐 多語言支援
#### 透過 GitHub Action 支援 (自動化且保持最新)
[法文](../fr/README.md) | [西班牙文](../es/README.md) | [德文](../de/README.md) | [俄文](../ru/README.md) | [阿拉伯文](../ar/README.md) | [波斯文 (法爾西)](../fa/README.md) | [烏爾都文](../ur/README.md) | [中文 (簡體)](../zh/README.md) | [中文 (繁體，澳門)](./README.md) | [中文 (繁體，香港)](../hk/README.md) | [中文 (繁體，台灣)](../tw/README.md) | [日文](../ja/README.md) | [韓文](../ko/README.md) | [印地文](../hi/README.md) | [孟加拉文](../bn/README.md) | [馬拉地文](../mr/README.md) | [尼泊爾文](../ne/README.md) | [旁遮普文 (古木基文)](../pa/README.md) | [葡萄牙文 (葡萄牙)](../pt/README.md) | [葡萄牙文 (巴西)](../br/README.md) | [義大利文](../it/README.md) | [波蘭文](../pl/README.md) | [土耳其文](../tr/README.md) | [希臘文](../el/README.md) | [泰文](../th/README.md) | [瑞典文](../sv/README.md) | [丹麥文](../da/README.md) | [挪威文](../no/README.md) | [芬蘭文](../fi/README.md) | [荷蘭文](../nl/README.md) | [希伯來文](../he/README.md) | [越南文](../vi/README.md) | [印尼文](../id/README.md) | [馬來文](../ms/README.md) | [他加祿文 (菲律賓)](../tl/README.md) | [斯瓦希里文](../sw/README.md) | [匈牙利文](../hu/README.md) | [捷克文](../cs/README.md) | [斯洛伐克文](../sk/README.md) | [羅馬尼亞文](../ro/README.md) | [保加利亞文](../bg/README.md) | [塞爾維亞文 (西里爾字母)](../sr/README.md) | [克羅埃西亞文](../hr/README.md) | [斯洛維尼亞文](../sl/README.md) | [烏克蘭文](../uk/README.md) | [緬甸文 (緬甸)](../my/README.md)
[法文](../fr/README.md) | [西班牙文](../es/README.md) | [德文](../de/README.md) | [俄文](../ru/README.md) | [阿拉伯文](../ar/README.md) | [波斯文 (法爾西)](../fa/README.md) | [烏爾都文](../ur/README.md) | [中文 (簡體)](../zh/README.md) | [中文 (繁體，澳門)](./README.md) | [中文 (繁體，香港)](../hk/README.md) | [中文 (繁體，台灣)](../tw/README.md) | [日文](../ja/README.md) | [韓文](../ko/README.md) | [印地文](../hi/README.md) | [孟加拉文](../bn/README.md) | [馬拉地文](../mr/README.md) | [尼泊爾文](../ne/README.md) | [旁遮普文 (古木基文)](../pa/README.md) | [葡萄牙文 (葡萄牙)](../pt/README.md) | [葡萄牙文 (巴西)](../br/README.md) | [義大利文](../it/README.md) | [波蘭文](../pl/README.md) | [土耳其文](../tr/README.md) | [希臘文](../el/README.md) | [泰文](../th/README.md) | [瑞典文](../sv/README.md) | [丹麥文](../da/README.md) | [挪威文](../no/README.md) | [芬蘭文](../fi/README.md) | [荷蘭文](../nl/README.md) | [希伯來文](../he/README.md) | [越南文](../vi/README.md) | [印尼文](../id/README.md) | [馬來文](../ms/README.md) | [塔加洛文 (菲律賓)](../tl/README.md) | [斯瓦希里文](../sw/README.md) | [匈牙利文](../hu/README.md) | [捷克文](../cs/README.md) | [斯洛伐克文](../sk/README.md) | [羅馬尼亞文](../ro/README.md) | [保加利亞文](../bg/README.md) | [塞爾維亞文 (西里爾文)](../sr/README.md) | [克羅埃西亞文](../hr/README.md) | [斯洛維尼亞文](../sl/README.md) | [烏克蘭文](../uk/README.md) | [緬甸文 (緬甸)](../my/README.md)
**如果您希望支援其他語言，請參考 [此處](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) 列出的支援語言**
**如果希望支援其他語言，請參考 [此處](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## 加入社群
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -53,16 +53,16 @@ CO_OP_TRANSLATOR_METADATA:
我們不會在這門課程中涵蓋：
> [在 Microsoft Learn 集合中找到所有額外的課程資源](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [在 Microsoft Learn 的課程集合中找到所有額外資源](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **人工智慧在商業中的應用案例**。建議參加 [商業用戶的人工智慧入門](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，或由 [INSEAD](https://www.insead.edu/) 合作開發的 [AI 商業學院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)。
* **人工智慧在商業中的應用案例**。建議參加 [商業使用者的人工智慧入門](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，或 [人工智慧商業學院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)，由 [INSEAD](https://www.insead.edu/) 合作開發。
* **經典機器學習**，這在我們的 [機器學習入門課程](http://github.com/Microsoft/ML-for-Beginners) 中有詳細描述。
* 使用 **[認知服務](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** 建立的實際人工智慧應用。建議從 Microsoft Learn 的模組開始，例如 [視覺](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然語言處理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[Azure OpenAI Service 的生成式人工智慧](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 等。
* 特定的機器學習 **雲端框架**，例如 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) 或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。建議使用 [Azure Machine Learning 建立和操作機器學習解決方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 和 [Azure Databricks 建立和操作機器學習解決方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
* 使用 **[認知服務](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** 建立的實際人工智慧應用。建議從 Microsoft Learn 的模組開始，例如 [影像](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然語言處理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[Azure OpenAI Service 的生成式人工智慧](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 等。
* 特定的機器學習 **雲端框架**，例如 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)、或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。建議使用 [Azure Machine Learning 建立和操作機器學習解決方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 和 [Azure Databricks 建立和操作機器學習解決方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
* **對話式人工智慧** 和 **聊天機器人**。有一個單獨的 [建立對話式人工智慧解決方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，您也可以參考 [這篇部落格文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) 了解更多細節。
* **深度學習的數學基礎**。建議參考 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 所著的 [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)，此書也可在線上取得：[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
* **深度學習的數學基礎**。建議參考 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 所著的 [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)，也可在線上取得 [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
若想輕鬆入門 _雲端人工智慧_ 主題，建議參加 [Azure 人工智慧入門](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
若想輕鬆入門 _雲端人工智慧_ 主題，可考慮參加 [Azure 人工智慧入門](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
# 課程內容
@ -76,62 +76,61 @@ CO_OP_TRANSLATOR_METADATA:
| III | [**神經網路簡介**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [感知器](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [筆記本](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [實驗室](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [多層感知器與建立我們自己的框架](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [筆記本](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [實驗室](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [框架介紹（PyTorch/TensorFlow）與過度擬合](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [實驗](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| 05 | [框架入門（PyTorch/TensorFlow）與過擬合](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [實驗](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**電腦視覺**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [探索 Microsoft Azure 上的電腦視覺](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [電腦視覺介紹. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [筆記本](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [實驗](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 06 | [電腦視覺入門. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [筆記本](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [實驗](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [卷積神經網絡](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN 架構](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [實驗](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [預訓練網絡與遷移學習](./lessons/4-ComputerVision/08-TransferLearning/README.md) 和 [訓練技巧](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [實驗](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [自編碼器與變分自編碼器（VAEs）](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [生成對抗網絡（GANs）與藝術風格遷移](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [物件偵測](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [實驗](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 09 | [自編碼器與變分自編碼器 (VAEs)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [生成對抗網絡 (GANs) 與藝術風格遷移](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [物體檢測](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [實驗](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [語義分割. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**自然語言處理**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [探索 Microsoft Azure 上的自然語言處理](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [文本表示. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [語義詞嵌入. Word2Vec 和 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [語言建模. 訓練自己的嵌入](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [實驗](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [循環神經網絡（RNNs）](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成型循環網絡](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [實驗](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformer. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [命名實體識別（NER）](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [實驗](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大型語言模型、提示編程與少樣本任務](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [文本表示. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [語義詞嵌入. Word2Vec 和 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [語言建模. 訓練自己的嵌入](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [實驗](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [循環神經網絡 (RNN)](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成式循環網絡](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [實驗](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformer. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [命名實體識別 (NER)](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [實驗](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大型語言模型、提示編程與少樣本任務](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **其他 AI 技術** || |
| 21 | [遺傳算法](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [筆記本](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [深度強化學習](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [實驗](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [多代理系統](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| 23 | [多智能體系統](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI 倫理** | | |
| 24 | [AI 倫理與負責任的 AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: 負責任的 AI 原則](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **額外內容** | | |
| IX | **附加內容** | | |
| 25 | [多模態網絡、CLIP 和 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [筆記本](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## 每個課程包含
## 每節課包含
* 預讀材料
* 可執行的 Jupyter 筆記本，通常針對特定框架（**PyTorch** 或 **TensorFlow**）。可執行的筆記本還包含大量理論材料，因此要理解主題，您需要至少完成一個版本的筆記本（PyTorch 或 TensorFlow）。
* **實驗**（Labs）可用於某些主題，讓您有機會將所學材料應用於特定問題。
* 部分章節包含指向 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模組的連結，涵蓋相關主題。
* 可執行的 Jupyter 筆記本，通常針對特定框架（**PyTorch** 或 **TensorFlow**）。這些筆記本還包含大量理論內容，因此要理解主題，至少需要學習一個版本的筆記本（PyTorch 或 TensorFlow）。
* **實驗**：部分主題提供實驗，讓你有機會將所學應用於具體問題。
* 某些章節包含指向 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模組的鏈接，涵蓋相關主題。
## 開始使用
## 開始學習
- 我們已創建 [設置課程](./lessons/0-course-setup/setup.md)，幫助您設置開發環境。 - 對於教育工作者，我們也創建了 [課程設置指南](./lessons/0-course-setup/for-teachers.md)！
- 我們準備了一個 [設置課程](./lessons/0-course-setup/setup.md)，幫助你設置開發環境。
- 對於教育者，我們還準備了一個 [課程設置指南](./lessons/0-course-setup/for-teachers.md)！
- 如何 [在 VSCode 或 Codepace 中運行代碼](./lessons/0-course-setup/how-to-run.md)
請按照以下步驟：
按照以下步驟操作：
分叉（Fork）倉庫：點擊此頁面右上角的 "Fork" 按鈕。
克隆（Clone）倉庫：`git clone https://github.com/microsoft/AI-For-Beginners.git`
別忘了給此倉庫加星（🌟），以便日後更容易找到。
1. Fork 此倉庫：點擊頁面右上角的 "Fork" 按鈕。
2. 克隆倉庫：`git clone https://github.com/microsoft/AI-For-Beginners.git`
3. 別忘了給這個倉庫加星標（🌟），方便以後找到。
## 與其他學習者交流
加入我們的 [官方 AI Discord 伺服器](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)，與其他學習者交流並獲得支持。
如果您在構建過程中有產品反饋或問題，請訪問我們的 [Azure AI Foundry 開發者論壇](https://aka.ms/foundry/forum)
如果在構建過程中有產品反饋或問題，請訪問我們的 [Azure AI Foundry 開發者論壇](https://aka.ms/foundry/forum)
## 測驗
> **關於測驗的注意事項**：所有測驗都包含在 Quiz-app 資料夾中，位於 etc\quiz-app，或[線上版本](https://ff-quizzes.netlify.app/)。它們已在課程中連結，測驗應用程式可以在本地執行或部署到 Azure；請按照 `quiz-app` 資料夾中的指示操作。測驗正在逐步進行本地化。
## 幫助需求
> **關於測驗的說明**：所有測驗都包含在 Quiz-app 資料夾中，位於 etc\quiz-app，或[線上版本](https://ff-quizzes.netlify.app/)。它們已在課程中連結，測驗應用程式可以在本地執行或部署到 Azure；請按照 `quiz-app` 資料夾中的指示操作。測驗正在逐步進行本地化。
## 幫助徵求
您有任何建議或發現拼寫或程式碼錯誤嗎？請提交一個問題或建立一個拉取請求。
@ -147,22 +146,22 @@ CO_OP_TRANSLATOR_METADATA:
我們的團隊還製作了其他課程！請查看以下內容：
- [生成式 AI 初學者課程](https://aka.ms/genai-beginners)
- [生成式 AI 初學者課程 .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [生成式 AI 入門](https://aka.ms/genai-beginners)
- [生成式 AI 入門 .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [使用 JavaScript 的生成式 AI](https://github.com/microsoft/generative-ai-with-javascript)
- [使用 Java 的生成式 AI](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI 初學者課程](https://aka.ms/ai-beginners)
- [資料科學初學者課程](https://aka.ms/datascience-beginners)
- [機器學習初學者課程](https://aka.ms/ml-beginners)
- [網路安全初學者課程](https://github.com/microsoft/Security-101)
- [網頁開發初學者課程](https://aka.ms/webdev-beginners)
- [物聯網初學者課程](https://aka.ms/iot-beginners)
- [XR 開發初學者課程](https://github.com/microsoft/xr-development-for-beginners)
- [AI 入門](https://aka.ms/ai-beginners)
- [資料科學入門](https://aka.ms/datascience-beginners)
- [機器學習入門](https://aka.ms/ml-beginners)
- [網路安全入門](https://github.com/microsoft/Security-101)
- [網頁開發入門](https://aka.ms/webdev-beginners)
- [物聯網入門](https://aka.ms/iot-beginners)
- [XR 開發入門](https://github.com/microsoft/xr-development-for-beginners)
- [精通 GitHub Copilot 的智能應用](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [精通 GitHub Copilot 的 C#/.NET 開發者課程](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [選擇你的 Copilot 冒險之旅](https://github.com/microsoft/CopilotAdventures)
- [精通 GitHub Copilot 的 C#/.NET 開發者指南](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [選擇你的 Copilot 冒險](https://github.com/microsoft/CopilotAdventures)
---
**免責聲明**：
本文件使用 AI 翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原始語言的文件作為權威來源。對於關鍵資訊，建議尋求專業人工翻譯。我們對因使用此翻譯而產生的任何誤解或錯誤解讀概不負責。
本文件使用 AI 翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原始語言的文件作為權威來源。對於關鍵資訊，建議尋求專業人工翻譯。我們對於因使用此翻譯而產生的任何誤解或錯誤解讀概不負責。

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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# नवशिक्यांसाठी कृत्रिम बुद्धिमत्ता - अभ्यासक्रम
# नवशिक्यांसाठी कृत्रिम बुद्धिमत्ता - अभ्यासक्रम
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.mr.png)|
|:---:|
| नवशिक्यांसाठी AI - _[@girlie_mac](https://twitter.com/girlie_mac) यांचे स्केच नोट_ |
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.mr.png)|
|:---:|
| नवशिक्यांसाठी AI - _[@girlie_mac](https://twitter.com/girlie_mac) यांचे स्केच_ |
**कृत्रिम बुद्धिमत्ता** (AI) च्या जगात 12 आठवड्यांचा, 24 धड्यांचा अभ्यासक्रम शोधा! यात प्रात्यक्षिक धडे, प्रश्नमंजुषा आणि प्रयोगशाळा समाविष्ट आहेत. हा अभ्यासक्रम नवशिक्यांसाठी अनुकूल आहे आणि TensorFlow आणि PyTorch यांसारख्या साधनांसह AI मधील नैतिकतेचा समावेश करतो.
**कृत्रिम बुद्धिमत्ता** (AI) च्या जगात प्रवेश करा आमच्या 12 आठवड्यांच्या, 24 धड्यांच्या अभ्यासक्रमासह! यात व्यावहारिक धडे, प्रश्नमंजूषा आणि प्रयोगशाळा समाविष्ट आहेत. हा अभ्यासक्रम नवशिक्यांसाठी सोपा आहे आणि TensorFlow आणि PyTorch यांसारख्या साधनांसह AI मधील नैतिकतेवरही प्रकाश टाकतो.
### 🌐 बहुभाषिक समर्थन
### 🌐 बहुभाषिक समर्थन
#### GitHub Action द्वारे समर्थित (स्वयंचलित आणि नेहमी अद्ययावत)
#### GitHub Action द्वारे समर्थित (स्वयंचलित आणि नेहमी अद्ययावत)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](./README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](./README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**जर तुम्हाला अतिरिक्त भाषांमध्ये भाषांतर हवे असेल, तर समर्थित भाषांची यादी [येथे](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) पाहा.**
**जर तुम्हाला अतिरिक्त भाषांमध्ये भाषांतर हवे असेल तर समर्थित भाषांची यादी [येथे](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) दिली आहे.**
## समुदायामध्ये सामील व्हा
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## तुम्ही काय शिकाल
## तुम्ही काय शिकाल
**[अभ्यासक्रमाचा मनोमनी नकाशा](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[अभ्यासक्रमाचा मनाचा नकाशा](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
या अभ्यासक्रमात, तुम्ही शिकाल:
या अभ्यासक्रमात तुम्ही शिकाल:
* कृत्रिम बुद्धिमत्तेचे विविध दृष्टिकोन, ज्यामध्ये **ज्ञानाचे प्रतिनिधित्व** आणि तर्क यांसह "जुने चांगले" प्रतीकात्मक दृष्टिकोन ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)) समाविष्ट आहे.
* कृत्रिम बुद्धिमत्तेचे विविध दृष्टिकोन, ज्यामध्ये "चांगले जुने" प्रतीकात्मक दृष्टिकोन समाविष्ट आहे ज्यामध्ये **ज्ञानाचे प्रतिनिधित्व** आणि तर्क ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)) आहे.
* **न्यूरल नेटवर्क्स** आणि **डीप लर्निंग**, जे आधुनिक AI च्या केंद्रस्थानी आहेत. आम्ही या महत्त्वाच्या विषयांमागील संकल्पना दोन लोकप्रिय फ्रेमवर्क - [TensorFlow](http://Tensorflow.org) आणि [PyTorch](http://pytorch.org) च्या कोडसह स्पष्ट करू.
* प्रतिमा आणि मजकूरावर काम करण्यासाठी **न्यूरल आर्किटेक्चर्स**. आम्ही अलीकडील मॉडेल्स कव्हर करू, परंतु अत्याधुनिकतेत थोडी कमतरता असू शकते.
* कमी लोकप्रिय AI दृष्टिकोन, जसे की **जेनेटिक अल्गोरिदम्स** आणि **मल्टी-एजंट सिस्टीम्स**.
* प्रतिमा आणि मजकूरावर काम करण्यासाठी **न्यूरल आर्किटेक्चर्स**. आम्ही अलीकडील मॉडेल्स कव्हर करू परंतु अत्याधुनिक तंत्रज्ञान थोडे कमी असू शकते.
* कमी लोकप्रिय AI दृष्टिकोन, जसे की **Genetic Algorithms** आणि **Multi-Agent Systems**.
या अभ्यासक्रमात आम्ही कव्हर करणार नाही:
या अभ्यासक्रमात आम्ही काय कव्हर करणार नाही:
> [या अभ्यासक्रमासाठी सर्व अतिरिक्त संसाधने आमच्या Microsoft Learn संग्रहात शोधा](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [या अभ्यासक्रमासाठी सर्व अतिरिक्त संसाधने Microsoft Learn संग्रहामध्ये शोधा](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **व्यवसायातील AI चा वापर** याचे व्यवसाय प्रकरणे. [व्यवसाय वापरकर्त्यांसाठी AI ची ओळख](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) शिकण्याचा मार्ग किंवा [AI बिझनेस स्कूल](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), [INSEAD](https://www.insead.edu/) सह विकसित केलेला, यावर विचार करा.
* **क्लासिक मशीन लर्निंग**, जे आमच्या [नवशिक्यांसाठी मशीन लर्निंग अभ्यासक्रम](http://github.com/Microsoft/ML-for-Beginners) मध्ये चांगल्या प्रकारे वर्णन केले आहे.
* **[कॉग्निटिव्ह सर्व्हिसेस](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** वापरून तयार केलेल्या व्यावहारिक AI अनुप्रयोगांसाठी, [दृष्टी](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [नैसर्गिक भाषा प्रक्रिया](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI सेवा](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** आणि इतरांसाठी Microsoft Learn मॉड्यूल्ससह प्रारंभ करण्याची शिफारस करतो.
* विशिष्ट ML **क्लाउड फ्रेमवर्क्स**, जसे की [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), किंवा [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). [Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) आणि [Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) शिकण्याचे मार्ग वापरण्याचा विचार करा.
* **संवादी AI** आणि **चॅट बॉट्स**. यासाठी, [संवादी AI सोल्यूशन्स तयार करा](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) शिकण्याचा मार्ग आहे, तसेच [या ब्लॉग पोस्टला](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) अधिक तपशीलांसाठी संदर्भित करू शकता.
* **डीप लर्निंगमागील गणितीय संकल्पना**. यासाठी, Ian Goodfellow, Yoshua Bengio आणि Aaron Courville यांचे [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) वाचण्याची शिफारस करतो, जे [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) येथे ऑनलाइन उपलब्ध आहे.
* **व्यवसायातील AI** चा वापर करण्याचे व्यवसाय प्रकरण. Microsoft Learn वर [व्यवसाय वापरकर्त्यांसाठी AI ची ओळख](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) शिकण्याचा मार्ग किंवा [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), [INSEAD](https://www.insead.edu/) सह विकसित केलेला विचार करा.
* **क्लासिक मशीन लर्निंग**, जे आमच्या [नवशिक्यांसाठी मशीन लर्निंग अभ्यासक्रम](http://github.com/Microsoft/ML-for-Beginners) मध्ये चांगले वर्णन केले आहे.
* **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** वापरून तयार केलेले व्यावहारिक AI अनुप्रयोग. यासाठी, आम्ही Microsoft Learn मधील [दृष्टी](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [नैसर्गिक भाषा प्रक्रिया](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI Service सह जनरेटिव्ह AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** आणि इतरांसाठी मॉड्यूल्ससह प्रारंभ करण्याची शिफारस करतो.
* विशिष्ट ML **Cloud Frameworks**, जसे की [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), किंवा [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). [Azure Machine Learning सह मशीन लर्निंग सोल्यूशन्स तयार करा आणि ऑपरेट करा](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) आणि [Azure Databricks सह मशीन लर्निंग सोल्यूशन्स तयार करा आणि ऑपरेट करा](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) शिकण्याचे मार्ग विचारात घ्या.
* **संवादी AI** आणि **चॅट बॉट्स**. [संवादी AI सोल्यूशन्स तयार करा](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) शिकण्याचा मार्ग वेगळा आहे, आणि अधिक तपशीलांसाठी तुम्ही [हा ब्लॉग पोस्ट](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) देखील पाहू शकता.
* **डीप लर्निंगमधील गणितीय संकल्पना**. यासाठी, आम्ही Ian Goodfellow, Yoshua Bengio आणि Aaron Courville यांचे [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) शिफारस करतो, जे [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) वर ऑनलाइन उपलब्ध आहे.
_क्लाउडमधील AI_ विषयांची सौम्य ओळख मिळवण्यासाठी, [Azure वर कृत्रिम बुद्धिमत्तेसह प्रारंभ करा](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) शिकण्याचा मार्ग घ्या.
_क्लाउडमधील AI_ विषयांमध्ये सौम्य परिचयासाठी तुम्ही [Azure वर कृत्रिम बुद्धिमत्तेसह प्रारंभ करा](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) शिकण्याचा मार्ग विचारात घेऊ शकता.
# सामग्री
# सामग्री
| | धड्याचा दुवा | PyTorch/Keras/TensorFlow | प्रयोगशाळा |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [अभ्यासक्रम सेटअप](./lessons/0-course-setup/setup.md) | [तुमचे विकास वातावरण सेट करा](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI ची ओळख**](./lessons/1-Intro/README.md) | | |
| 01 | [AI ची ओळख आणि इतिहास](./lessons/1-Intro/README.md) | - | - |
| II | **प्रतीकात्मक AI** |
| 02 | [ज्ञानाचे प्रतिनिधित्व आणि तज्ज्ञ प्रणाली](./lessons/2-Symbolic/README.md) | [तज्ज्ञ प्रणाली](./lessons/2-Symbolic/Animals.ipynb) / [ऑन्टोलॉजी](./lessons/2-Symbolic/FamilyOntology.ipynb) /[संकल्प ग्राफ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**न्यूरल नेटवर्क्सची ओळख**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [परसेप्ट्रॉन](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [नोटबुक](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [प्रयोगशाळा](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [मल्टी-लेयर्ड परसेप्ट्रॉन आणि आपले स्वतःचे फ्रेमवर्क तयार करणे](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [नोटबुक](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [प्रयोगशाळा](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [फ्रेमवर्क्सची ओळख (PyTorch/TensorFlow) आणि ओव्हरफिटिंग](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [प्रयोगशाळा](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**कंप्युटर व्हिजन**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [मायक्रोसॉफ्ट Azure वर कंप्युटर व्हिजन एक्सप्लोर करा](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| | धड्याचा दुवा | PyTorch/Keras/TensorFlow | प्रयोगशाळा |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [अभ्यासक्रम सेटअप](./lessons/0-course-setup/setup.md) | [तुमचे विकास वातावरण सेट करा](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI ची ओळख**](./lessons/1-Intro/README.md) | | |
| 01 | [AI ची ओळख आणि इतिहास](./lessons/1-Intro/README.md) | - | - |
| II | **प्रतीकात्मक AI** |
| 02 | [ज्ञानाचे प्रतिनिधित्व आणि तज्ज्ञ प्रणाली](./lessons/2-Symbolic/README.md) | [तज्ज्ञ प्रणाली](./lessons/2-Symbolic/Animals.ipynb) / [ऑन्टोलॉजी](./lessons/2-Symbolic/FamilyOntology.ipynb) /[संकल्प ग्राफ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**न्यूरल नेटवर्क्सची ओळख**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [मल्टी-लेयर्ड Perceptron आणि आपले स्वतःचे फ्रेमवर्क तयार करणे](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [फ्रेमवर्क्स (PyTorch/TensorFlow) आणि ओव्हरफिटिंगची ओळख](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [प्रयोगशाळा](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**कंप्युटर व्हिजन**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure वर कंप्युटर व्हिजन एक्सप्लोर करा](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [कंप्युटर व्हिजनची ओळख. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [नोटबुक](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [प्रयोगशाळा](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [कन्फ्युलेशनल न्यूरल नेटवर्क्स](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN आर्किटेक्चर्स](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [प्रयोगशाळा](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [प्री-ट्रेंड नेटवर्क्स आणि ट्रान्सफर लर्निंग](./lessons/4-ComputerVision/08-TransferLearning/README.md) आणि [ट्रेनिंग ट्रिक्स](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [प्रयोगशाळा](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [ऑटोएन्कोडर्स आणि VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 07 | [कॉनव्होल्यूशनल न्यूरल नेटवर्क्स](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN आर्किटेक्चर्स](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [प्रयोगशाळा](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [पूर्व-प्रशिक्षित नेटवर्क्स आणि ट्रान्सफर लर्निंग](./lessons/4-ComputerVision/08-TransferLearning/README.md) आणि [प्रशिक्षण युक्त्या](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [प्रयोगशाळा](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [ऑटोएनकोडर्स आणि VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [जनरेटिव्ह अॅडव्हर्सेरियल नेटवर्क्स आणि आर्टिस्टिक स्टाइल ट्रान्सफर](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [ऑब्जेक्ट डिटेक्शन](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [प्रयोगशाळा](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [सेमॅंटिक सेगमेंटेशन. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**नॅचरल लँग्वेज प्रोसेसिंग**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [मायक्रोसॉफ्ट Azure वर नॅचरल लँग्वेज प्रोसेसिंग एक्सप्लोर करा](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [टेक्स्ट रिप्रेझेंटेशन. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [सेमॅंटिक वर्ड एम्बेडिंग्ज. Word2Vec आणि GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [लँग्वेज मॉडेलिंग. स्वतःचे एम्बेडिंग्ज तयार करा](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [प्रयोगशाळा](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [रिकरंट न्यूरल नेटवर्क्स](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [जनरेटिव्ह रिकरंट नेटवर्क्स](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [प्रयोगशाळा](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ट्रान्सफॉर्मर्स. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [नेम्ड एंटिटी रिकग्निशन](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [प्रयोगशाळा](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [मोठे लँग्वेज मॉडेल्स, प्रॉम्प्ट प्रोग्रामिंग आणि फ्यू-शॉट टास्क्स](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **इतर AI तंत्रज्ञान** || |
| 12 | [सिमॅंटिक सेगमेंटेशन. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**नॅचरल लँग्वेज प्रोसेसिंग**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure वर नॅचरल लँग्वेज प्रोसेसिंग एक्सप्लोर करा](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [टेक्स्ट रिप्रेझेंटेशन. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [सिमॅंटिक वर्ड एम्बेडिंग्स. Word2Vec आणि GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [लँग्वेज मॉडेलिंग. स्वतःचे एम्बेडिंग्स प्रशिक्षण द्या](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [प्रयोगशाळा](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [रिकरंट न्यूरल नेटवर्क्स](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [जनरेटिव्ह रिकरंट नेटवर्क्स](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [प्रयोगशाळा](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ट्रान्सफॉर्मर्स. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [नेम्ड एंटिटी रिकग्निशन](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [प्रयोगशाळा](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [मोठे भाषा मॉडेल्स, प्रॉम्प्ट प्रोग्रामिंग आणि फ्यू-शॉट टास्क्स](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **इतर AI तंत्र** || |
| 21 | [जेनेटिक अल्गोरिदम्स](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [नोटबुक](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [डीप रिइन्फोर्समेंट लर्निंग](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [प्रयोगशाळा](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [मल्टी-एजंट सिस्टीम्स](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
@ -106,31 +106,31 @@ _क्लाउडमधील AI_ विषयांची सौम्य ओ
## प्रत्येक धड्यात समाविष्ट आहे
* पूर्व-वाचन साहित्य
* कार्यक्षम Jupyter नोटबुक्स, जे प्रामुख्याने फ्रेमवर्क (**PyTorch** किंवा **TensorFlow**) साठी विशिष्ट असतात. कार्यक्षम नोटबुकमध्ये बऱ्याच प्रमाणात सैद्धांतिक सामग्री असते, त्यामुळे विषय समजून घेण्यासाठी तुम्हाला किमान एक नोटबुक (PyTorch किंवा TensorFlow) वाचणे आवश्यक आहे.
* **प्रयोगशाळा** काही विषयांसाठी उपलब्ध आहेत, ज्या तुम्हाला शिकलेल्या सामग्रीचा विशिष्ट समस्यांवर उपयोग करण्याची संधी देतात.
* काही विभागांमध्ये [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) मॉड्यूल्सचे दुवे आहेत, जे संबंधित विषयांवर प्रकाश टाकतात.
* कार्यक्षम Jupyter नोटबुक्स, जे फ्रेमवर्क (**PyTorch** किंवा **TensorFlow**) साठी विशिष्ट असतात. कार्यक्षम नोटबुकमध्ये बरेच सैद्धांतिक साहित्य असते, त्यामुळे विषय समजून घेण्यासाठी तुम्हाला किमान एक नोटबुक आवृत्ती (PyTorch किंवा TensorFlow) पाहणे आवश्यक आहे.
* **प्रयोगशाळा** काही विषयांसाठी उपलब्ध आहेत, ज्यामुळे तुम्ही शिकलेल्या साहित्याचा विशिष्ट समस्येवर उपयोग करण्याची संधी मिळते.
* काही विभागांमध्ये संबंधित विषयांवर [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) मॉड्यूल्सचे दुवे आहेत.
## सुरुवात कशी करावी
- तुमच्या विकास वातावरणाची सेटअप करण्यात मदत करण्यासाठी आम्ही [सेटअप धडा](./lessons/0-course-setup/setup.md) तयार केला आहे. - शिक्षकांसाठी, आम्ही [शिक्षकांसाठी अभ्यासक्रम सेटअप धडा](./lessons/0-course-setup/for-teachers.md) देखील तयार केला आहे!
- [VSCode किंवा Codepace मध्ये कोड कसा चालवायचा](./lessons/0-course-setup/how-to-run.md) याबद्दल जाणून घ्या.
- तुमच्या विकास वातावरणाची सेटअप करण्यासाठी आम्ही [सेटअप धडा](./lessons/0-course-setup/setup.md) तयार केला आहे. - शिक्षकांसाठी, आम्ही [शिक्षकांसाठी अभ्यासक्रम सेटअप धडा](./lessons/0-course-setup/for-teachers.md) देखील तयार केला आहे!
- [VSCode किंवा Codepace मध्ये कोड कसा चालवायचा](./lessons/0-course-setup/how-to-run.md)
या चरणांचे अनुसरण करा:
रेपॉजिटरी फोर्क करा: या पृष्ठाच्या वरच्या उजव्या कोपऱ्यातील "Fork" बटणावर क्लिक करा.
रेपॉझिटरी फॉर्क करा: या पृष्ठाच्या वरच्या उजव्या कोपऱ्यात "Fork" बटणावर क्लिक करा.
रेपॉजिटरी क्लोन करा: `git clone https://github.com/microsoft/AI-For-Beginners.git`
रेपॉझिटरी क्लोन करा: `git clone https://github.com/microsoft/AI-For-Beginners.git`
या रेपॉजिटरीला नंतर सोपे सापडण्यासाठी स्टार (🌟) करायला विसरू नका.
या रेपोला नंतर सोपे शोधण्यासाठी स्टार (🌟) करायला विसरू नका.
## इतर शिकणाऱ्यांना भेटा
आमच्या [अधिकृत AI Discord सर्व्हर](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) मध्ये सामील व्हा, जिथे तुम्ही या कोर्समध्ये सहभागी होणाऱ्या इतर शिकणाऱ्यांशी संवाद साधू शकता आणि मदत मिळवू शकता.
आमच्या [अधिकृत AI Discord सर्व्हर](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) मध्ये सामील व्हा, या कोर्समध्ये सहभागी होणाऱ्या इतर शिकणाऱ्यांना भेटा आणि नेटवर्क करा तसेच समर्थन मिळवा.
जर तुम्हाला उत्पादनाबद्दल अभिप्राय द्यायचा असेल किंवा तयार करताना काही प्रश्न असतील, तर आमच्या [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) ला भेट द्या.
जर तुम्हाला उत्पादन अभिप्राय किंवा प्रश्न असतील तर आमच्या [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) ला भेट द्या.
## क्विझेस
> **क्विझेसबद्दल एक टीप**: सर्व क्विझेस `Quiz-app` फोल्डरमध्ये `etc\quiz-app` मध्ये आहेत, किंवा [ऑनलाइन येथे](https://ff-quizzes.netlify.app/) उपलब्ध आहेत. त्या धड्यांमधून लिंक केलेल्या आहेत. `quiz-app` स्थानिक पातळीवर चालवता येते किंवा Azure वर तैनात करता येते; `quiz-app` फोल्डरमधील सूचनांचे पालन करा. त्या हळूहळू स्थानिक भाषेत अनुवादित केल्या जात आहेत.
> **क्विझेसबद्दल एक टीप**: सर्व क्विझेस Quiz-app फोल्डरमध्ये etc\quiz-app मध्ये आहेत, किंवा [ऑनलाइन येथे](https://ff-quizzes.netlify.app/) उपलब्ध आहेत. त्या धड्यांमधून लिंक केल्या आहेत. Quiz-app स्थानिक पातळीवर चालवता येतो किंवा Azure वर डिप्लॉय करता येतो; `quiz-app` फोल्डरमधील सूचनांचे पालन करा. त्या हळूहळू स्थानिक भाषेत अनुवादित केल्या जात आहेत.
## मदतीची आवश्यकता
तुमच्याकडे काही सूचना आहेत का किंवा तुम्हाला स्पेलिंग किंवा कोडमधील चुका सापडल्या आहेत का? कृपया एक इश्यू उघडा किंवा एक पुल रिक्वेस्ट तयार करा.
@ -145,7 +145,7 @@ _क्लाउडमधील AI_ विषयांची सौम्य ओ
## इतर अभ्यासक्रम
आमची टीम इतर अभ्यासक्रम देखील तयार करते! येथे पहा:
आमची टीम इतर अभ्यासक्रम तयार करते! येथे पहा:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
@ -165,4 +165,4 @@ _क्लाउडमधील AI_ विषयांची सौम्य ओ
---
**अस्वीकरण**:
हा दस्तऐवज AI भाषांतर सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) चा वापर करून भाषांतरित करण्यात आला आहे. आम्ही अचूकतेसाठी प्रयत्नशील असलो तरी, कृपया लक्षात घ्या की स्वयंचलित भाषांतरांमध्ये त्रुटी किंवा अचूकतेचा अभाव असू शकतो. मूळ भाषेतील दस्तऐवज हा अधिकृत स्रोत मानला जावा. महत्त्वाच्या माहितीसाठी व्यावसायिक मानवी भाषांतराची शिफारस केली जाते. या भाषांतराचा वापर केल्यामुळे उद्भवणाऱ्या कोणत्याही गैरसमजांकरिता किंवा चुकीच्या अर्थ लावण्याकरिता आम्ही जबाबदार राहणार नाही.
हा दस्तऐवज AI भाषांतर सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) वापरून भाषांतरित करण्यात आला आहे. आम्ही अचूकतेसाठी प्रयत्नशील असलो तरी कृपया लक्षात ठेवा की स्वयंचलित भाषांतरांमध्ये त्रुटी किंवा अचूकतेचा अभाव असू शकतो. मूळ भाषेतील दस्तऐवज हा अधिकृत स्रोत मानावा. महत्त्वाच्या माहितीसाठी व्यावसायिक मानवी भाषांतराची शिफारस केली जाते. या भाषांतराचा वापर करून निर्माण होणाऱ्या कोणत्याही गैरसमज किंवा चुकीच्या अर्थासाठी आम्ही जबाबदार राहणार नाही.

100
translations/ms/README.md
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@ -1,8 +1,8 @@
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"translation_date": "2025-09-07T14:02:19+00:00",
"source_file": "README.md",
"language_code": "ms"
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@ -35,7 +35,7 @@ Terokai dunia **Kecerdasan Buatan** (AI) dengan kurikulum 12 minggu, 24 pelajara
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](./README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Jika anda ingin menambah sokongan untuk bahasa lain, senarai bahasa yang disokong boleh didapati [di sini](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Jika anda ingin menambah sokongan bahasa tambahan, senarai bahasa yang disokong boleh didapati [di sini](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Sertai Komuniti
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -44,56 +44,56 @@ Terokai dunia **Kecerdasan Buatan** (AI) dengan kurikulum 12 minggu, 24 pelajara
**[Peta Minda Kursus](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
Dalam kurikulum ini, anda akan mempelajari:
Dalam kurikulum ini, anda akan belajar:
* Pendekatan berbeza terhadap Kecerdasan Buatan, termasuk pendekatan simbolik "lama" dengan **Perwakilan Pengetahuan** dan penaakulan ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Rangkaian Neural** dan **Pembelajaran Mendalam**, yang menjadi teras AI moden. Kami akan menerangkan konsep di sebalik topik penting ini menggunakan kod dalam dua rangka kerja paling popular - [TensorFlow](http://Tensorflow.org) dan [PyTorch](http://pytorch.org).
* **Seni Bina Neural** untuk bekerja dengan imej dan teks. Kami akan membincangkan model terkini tetapi mungkin kurang dalam keadaan seni terkini.
* Pendekatan AI yang kurang popular, seperti **Algoritma Genetik** dan **Sistem Berbilang Agen**.
* Pendekatan berbeza terhadap Kecerdasan Buatan, termasuk pendekatan simbolik "lama yang baik" dengan **Perwakilan Pengetahuan** dan penaakulan ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Rangkaian Neural** dan **Pembelajaran Mendalam**, yang merupakan teras AI moden. Kami akan menggambarkan konsep di sebalik topik penting ini menggunakan kod dalam dua rangka kerja paling popular - [TensorFlow](http://Tensorflow.org) dan [PyTorch](http://pytorch.org).
* **Seni Bina Neural** untuk bekerja dengan imej dan teks. Kami akan merangkumi model terkini tetapi mungkin sedikit kekurangan dalam teknologi terkini.
* Pendekatan AI yang kurang popular, seperti **Algoritma Genetik** dan **Sistem Multi-Ejen**.
Apa yang tidak akan kami bahas dalam kurikulum ini:
> [Cari semua sumber tambahan untuk kursus ini dalam koleksi Microsoft Learn kami](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Kes perniagaan menggunakan **AI dalam Perniagaan**. Pertimbangkan untuk mengambil laluan pembelajaran [Pengenalan kepada AI untuk pengguna perniagaan](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) di Microsoft Learn, atau [Sekolah Perniagaan AI](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), yang dibangunkan bersama dengan [INSEAD](https://www.insead.edu/).
* Kes perniagaan menggunakan **AI dalam Perniagaan**. Pertimbangkan untuk mengambil laluan pembelajaran [Pengenalan kepada AI untuk pengguna perniagaan](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) di Microsoft Learn, atau [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), yang dibangunkan dengan kerjasama [INSEAD](https://www.insead.edu/).
* **Pembelajaran Mesin Klasik**, yang dijelaskan dengan baik dalam [Kurikulum Pembelajaran Mesin untuk Pemula](http://github.com/Microsoft/ML-for-Beginners).
* Aplikasi AI praktikal yang dibina menggunakan **[Perkhidmatan Kognitif](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Untuk ini, kami mengesyorkan anda bermula dengan modul Microsoft Learn untuk [penglihatan](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [pemprosesan bahasa semula jadi](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[AI Generatif dengan Perkhidmatan Azure OpenAI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** dan lain-lain.
* Rangka Kerja Awan ML tertentu, seperti [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), atau [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Pertimbangkan untuk menggunakan laluan pembelajaran [Bina dan kendalikan penyelesaian pembelajaran mesin dengan Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) dan [Bina dan Kendalikan Penyelesaian Pembelajaran Mesin dengan Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* Aplikasi AI praktikal yang dibina menggunakan **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Untuk ini, kami mengesyorkan anda bermula dengan modul Microsoft Learn untuk [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI dengan Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** dan lain-lain.
* Rangka kerja **Cloud ML** tertentu, seperti [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), atau [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Pertimbangkan untuk menggunakan laluan pembelajaran [Bangunkan dan operasikan penyelesaian pembelajaran mesin dengan Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) dan [Bangunkan dan Operasikan Penyelesaian Pembelajaran Mesin dengan Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI Perbualan** dan **Chat Bots**. Terdapat laluan pembelajaran berasingan [Cipta penyelesaian AI perbualan](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), dan anda juga boleh merujuk kepada [catatan blog ini](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) untuk maklumat lanjut.
* **Matematik Mendalam** di sebalik pembelajaran mendalam. Untuk ini, kami mengesyorkan [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) oleh Ian Goodfellow, Yoshua Bengio dan Aaron Courville, yang juga tersedia dalam talian di [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Untuk pengenalan yang mudah kepada topik _AI dalam Awan_, anda boleh mempertimbangkan untuk mengambil Laluan Pembelajaran [Bermula dengan kecerdasan buatan di Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
Untuk pengenalan lembut kepada topik _AI dalam Cloud_, anda boleh mempertimbangkan untuk mengambil laluan pembelajaran [Mulakan dengan kecerdasan buatan di Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Kandungan
| | Pautan Pelajaran | PyTorch/Keras/TensorFlow | Makmal |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Persediaan Kursus](./lessons/0-course-setup/setup.md) | [Sediakan Persekitaran Pembangunan Anda](./lessons/0-course-setup/how-to-run.md) | |
| 0 | [Persediaan Kursus](./lessons/0-course-setup/setup.md) | [Persediaan Persekitaran Pembangunan Anda](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Pengenalan kepada AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Pengenalan dan Sejarah AI](./lessons/1-Intro/README.md) | - | - |
| II | **AI Simbolik** |
| 02 | [Perwakilan Pengetahuan dan Sistem Pakar](./lessons/2-Symbolic/README.md) | [Sistem Pakar](./lessons/2-Symbolic/Animals.ipynb) / [Ontologi](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Graf Konsep](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Pengenalan kepada Rangkaian Neural**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Makmal](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Perceptron Berlapis Pelbagai dan Mencipta Rangka Kerja Sendiri](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Makmal](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Pengenalan kepada Rangka Kerja (PyTorch/TensorFlow) dan Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| 04 | [Perceptron Berlapis Pelbagai dan Membina Rangka Kerja Kita Sendiri](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Makmal](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Pengenalan kepada Frameworks (PyTorch/TensorFlow) dan Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Penglihatan Komputer**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Terokai Penglihatan Komputer di Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Pengenalan kepada Penglihatan Komputer. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Rangkaian Neural Konvolusi](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Seni Bina CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Rangkaian Pra-latih dan Pembelajaran Pemindahan](./lessons/4-ComputerVision/08-TransferLearning/README.md) dan [Trik Latihan](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoder dan VAE](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 09 | [Autoencoder dan VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Rangkaian Adversarial Generatif & Pemindahan Gaya Artistik](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Pengesanan Objek](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Segmentasi Semantik. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Pemprosesan Bahasa Semula Jadi**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Terokai Pemprosesan Bahasa Semula Jadi di Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Perwakilan Teks. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Perwakilan Perkataan Semantik. Word2Vec dan GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Pemodelan Bahasa. Latih Perwakilan Anda Sendiri](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rangkaian Neural Berulang](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Rangkaian Berulang Generatif](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformer. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Pengecaman Entiti Bernama](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Model Bahasa Besar, Pengaturcaraan Prompt dan Tugas Few-Shot](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Representasi Teks. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Pembenaman perkataan semantik. Word2Vec dan GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Pemodelan Bahasa. Latih pembenaman anda sendiri](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rangkaian Neural Berulang](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Rangkaian Berulang Generatif](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Pengecaman Entiti Bernama](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Model Bahasa Besar, Pengaturcaraan Prompt dan Tugas Few-Shot](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Teknik AI Lain** || |
| 21 | [Algoritma Genetik](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Pembelajaran Pengukuhan Mendalam](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -106,8 +106,8 @@ Untuk pengenalan yang mudah kepada topik _AI dalam Awan_, anda boleh mempertimba
## Setiap pelajaran mengandungi
* Bahan bacaan awal
* Jupyter Notebook yang boleh dilaksanakan, yang sering khusus kepada rangka kerja (**PyTorch** atau **TensorFlow**). Notebook yang boleh dilaksanakan juga mengandungi banyak bahan teori, jadi untuk memahami topik ini anda perlu melalui sekurang-kurangnya satu versi notebook (sama ada PyTorch atau TensorFlow).
* **Lab** tersedia untuk beberapa topik, yang memberi anda peluang untuk mencuba menerapkan bahan yang telah anda pelajari kepada masalah tertentu.
* Jupyter Notebooks yang boleh dilaksanakan, yang sering khusus kepada framework (**PyTorch** atau **TensorFlow**). Notebook yang boleh dilaksanakan juga mengandungi banyak bahan teori, jadi untuk memahami topik ini anda perlu melalui sekurang-kurangnya satu versi notebook (sama ada PyTorch atau TensorFlow).
* **Labs** tersedia untuk beberapa topik, yang memberi anda peluang untuk mencuba menerapkan bahan yang telah anda pelajari kepada masalah tertentu.
* Beberapa bahagian mengandungi pautan ke modul [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) yang merangkumi topik berkaitan.
## Memulakan
@ -121,11 +121,11 @@ Fork Repositori: Klik pada butang "Fork" di sudut kanan atas halaman ini.
Clone Repositori: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Jangan lupa untuk memberi bintang (🌟) pada repo ini supaya lebih mudah ditemui kemudian.
Jangan lupa untuk memberi bintang (🌟) pada repo ini supaya lebih mudah mencarinya kemudian.
## Bertemu dengan Pelajar Lain
Sertai [pelayan Discord AI rasmi](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) kami untuk bertemu dan berhubung dengan pelajar lain yang mengikuti kursus ini dan mendapatkan sokongan.
Sertai [server Discord AI rasmi](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) kami untuk bertemu dan berhubung dengan pelajar lain yang mengikuti kursus ini serta mendapatkan sokongan.
Jika anda mempunyai maklum balas produk atau soalan semasa membina, lawati [Forum Pembangun Azure AI Foundry](https://aka.ms/foundry/forum)
@ -133,36 +133,36 @@ Jika anda mempunyai maklum balas produk atau soalan semasa membina, lawati [Foru
> **Nota mengenai kuiz**: Semua kuiz terdapat dalam folder Quiz-app di etc\quiz-app, atau [Online Di Sini](https://ff-quizzes.netlify.app/) Ia dihubungkan dari dalam pelajaran, aplikasi kuiz boleh dijalankan secara tempatan atau disebarkan ke Azure; ikuti arahan dalam folder `quiz-app`. Ia sedang dilokalkan secara beransur-ansur.
## Bantuan Diperlukan
Adakah anda mempunyai cadangan atau menemui kesalahan ejaan atau kod? Sila kemukakan isu atau buat permintaan tarik.
Adakah anda mempunyai cadangan atau menemui kesalahan ejaan atau kod? Sila buat isu atau cipta pull request.
## Terima Kasih Istimewa
## Penghargaan Khas
* **✍️ Penulis Utama:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Editor:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustrator Sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Pencipta Kuiz:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Penyumbang Teras:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ Penulis Utama:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Editor:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustrator Sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Pencipta Kuiz:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Penyumbang Teras:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Kurikulum Lain
Pasukan kami menghasilkan kurikulum lain! Lihat:
- [Generative AI untuk Pemula](https://aka.ms/genai-beginners)
- [Generative AI untuk Pemula .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI dengan JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI dengan Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI untuk Pemula](https://aka.ms/ai-beginners)
- [Data Science untuk Pemula](https://aka.ms/datascience-beginners)
- [ML untuk Pemula](https://aka.ms/ml-beginners)
- [Keselamatan Siber untuk Pemula](https://github.com/microsoft/Security-101)
- [Pembangunan Web untuk Pemula](https://aka.ms/webdev-beginners)
- [IoT untuk Pemula](https://aka.ms/iot-beginners)
- [Pembangunan XR untuk Pemula](https://github.com/microsoft/xr-development-for-beginners)
- [Menguasai GitHub Copilot untuk Penggunaan Agen](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Menguasai GitHub Copilot untuk Pembangun C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Pilih Pengembaraan Copilot Anda Sendiri](https://github.com/microsoft/CopilotAdventures)
- [Generative AI untuk Pemula](https://aka.ms/genai-beginners)
- [Generative AI untuk Pemula .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI dengan JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI dengan Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI untuk Pemula](https://aka.ms/ai-beginners)
- [Data Science untuk Pemula](https://aka.ms/datascience-beginners)
- [ML untuk Pemula](https://aka.ms/ml-beginners)
- [Keselamatan Siber untuk Pemula](https://github.com/microsoft/Security-101)
- [Pembangunan Web untuk Pemula](https://aka.ms/webdev-beginners)
- [IoT untuk Pemula](https://aka.ms/iot-beginners)
- [Pembangunan XR untuk Pemula](https://github.com/microsoft/xr-development-for-beginners)
- [Menguasai GitHub Copilot untuk Penggunaan Agen](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Menguasai GitHub Copilot untuk Pembangun C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Pilih Pengembaraan Copilot Anda Sendiri](https://github.com/microsoft/CopilotAdventures)
---
**Penafian**:
Dokumen ini telah diterjemahkan menggunakan perkhidmatan terjemahan AI [Co-op Translator](https://github.com/Azure/co-op-translator). Walaupun kami berusaha untuk memastikan ketepatan, sila ambil perhatian bahawa terjemahan automatik mungkin mengandungi kesilapan atau ketidaktepatan. Dokumen asal dalam bahasa asalnya harus dianggap sebagai sumber yang berwibawa. Untuk maklumat yang kritikal, terjemahan manusia profesional adalah disyorkan. Kami tidak bertanggungjawab atas sebarang salah faham atau salah tafsir yang timbul daripada penggunaan terjemahan ini.
Dokumen ini telah diterjemahkan menggunakan perkhidmatan terjemahan AI [Co-op Translator](https://github.com/Azure/co-op-translator). Walaupun kami berusaha untuk memastikan ketepatan, sila ambil maklum bahawa terjemahan automatik mungkin mengandungi kesilapan atau ketidaktepatan. Dokumen asal dalam bahasa asalnya harus dianggap sebagai sumber yang berwibawa. Untuk maklumat yang kritikal, terjemahan manusia profesional adalah disyorkan. Kami tidak bertanggungjawab atas sebarang salah faham atau salah tafsir yang timbul daripada penggunaan terjemahan ini.

101
translations/my/README.md
View File

@ -1,8 +1,8 @@
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"translation_date": "2025-09-07T14:15:17+00:00",
"source_file": "README.md",
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@ -27,15 +27,15 @@ CO_OP_TRANSLATOR_METADATA:
|:---:|
| AI For Beginners - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ |
**Artificial Intelligence** (AI) အပေါ် ၁၂ ပတ်၊ ၂၄ သင်ခန်းစာပါသော သင်ရိုးညွှန်းတမ်းကို လေ့လာပါ။ ၎င်းတွင် လက်တွေ့သင်ခန်းစာများ၊ စမ်းမေးခွန်းများနှင့် လက်တွေ့လေ့ကျင့်ခန်းများ ပါဝင်သည်။ သင်ရိုးညွှန်းတမ်းသည် အခြေခံအဆင့်အတွက် သင့်လျော်ပြီး TensorFlow နှင့် PyTorch ကိရိယာများ၊ AI အပေါ် သမိုင်းနှင့် ကျင့်ဝတ်များကိုလည်း ဖော်ပြထားသည်။
**Artificial Intelligence** (AI) အပေါ် ၁၂ ပတ်၊ ၂၄ သင်ခန်းစာပါသော သင်ရိုးညွှန်းတမ်းကို လေ့လာပါ။ ၎င်းတွင် လက်တွေ့သင်ခန်းစာများ၊ မေးခွန်းများနှင့် လက်တွေ့စမ်းသပ်မှုများပါဝင်သည်။ သင်ရိုးညွှန်းတမ်းသည် အခြေခံအဆင့်အတွက် သင့်လျော်ပြီး TensorFlow နှင့် PyTorch ကိရိယာများ၊ AI အပေါ် သမိုင်းနှင့် ကျင့်ဝတ်များကိုလည်း ဖော်ပြထားသည်။
### 🌐 ဘာသာစကားများပံ့ပိုးမှု
### 🌐 ဘာသာစကားများအထောက်အပံ့
#### GitHub Action မှတဆင့် အလိုအလျောက် (အမြဲနောက်ဆုံးအခြေအနေ)
#### GitHub Action မှတဆင့် အလိုအလျောက် (အမြဲနောက်ဆုံးအဆင့်)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](./README.md)
**အပိုဘာသာစကားများကို ပံ့ပိုးလိုပါက [ဒီနေရာ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) တွင် ရှာဖွေပါ။**
**အခြားဘာသာစကားများအထောက်အပံ့လိုအပ်ပါက [ဒီနေရာ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) တွင် ရှာဖွေပါ**
## အသိုင်းအဝိုင်းနှင့် ပူးပေါင်းပါ
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -47,37 +47,37 @@ CO_OP_TRANSLATOR_METADATA:
ဒီသင်ရိုးညွှန်းတမ်းတွင် သင်လေ့လာမည့်အရာများမှာ -
* Artificial Intelligence အပေါ် အမျိုးမျိုးသောနည်းလမ်းများ၊ အထူးသဖြင့် **Knowledge Representation** နှင့် reasoning ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)) အပါအဝင် "symbolic approach" ကိုလေ့လာပါ။
* **Neural Networks** နှင့် **Deep Learning** ကိုလေ့လာပါ။ ၎င်းသည် ခေတ်သစ် AI ၏ အခြေခံဖြစ်သည်။ TensorFlow နှင့် PyTorch ကိရိယာများကို အသုံးပြု၍ အဓိကအကြောင်းအရာများကို ရှင်းလင်းပြသမည်။
* **Neural Architectures** ကို ရုပ်ပုံများနှင့် စာသားများနှင့်အလုပ်လုပ်ရန်အတွက် အသုံးပြုပါမည်။
* **Neural Networks** နှင့် **Deep Learning**၊ ယခုခေတ် AI ၏ အခြေခံဖြစ်သော နည်းလမ်းများကို TensorFlow နှင့် PyTorch ကိရိယာများဖြင့် ရှင်းလင်းပြသပါမည်။
* **Neural Architectures** ကို ရုပ်ပုံများနှင့် စာသားများအတွက် အသုံးပြုခြင်း။ နောက်ဆုံးပေါ်နည်းလမ်းများကို ဖော်ပြမည်ဖြစ်သော်လည်း အချို့နည်းလမ်းများမှာ နောက်ဆုံးပေါ်နည်းလမ်းများထက် နည်းနည်းနောက်ကျနိုင်သည်။
* **Genetic Algorithms** နှင့် **Multi-Agent Systems** ကဲ့သို့သော နည်းလမ်းများကိုလည်း လေ့လာပါမည်။
ဒီသင်ရိုးညွှန်းတမ်းတွင် မပါဝင်မည့်အရာများ -
> [ဒီသင်ခန်းစာအတွက် Microsoft Learn collection တွင် အပိုအရင်းအမြစ်များကို ရှာဖွေပါ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [ဒီသင်ခန်းစာအတွက် Microsoft Learn collection တွင် အပိုဆောင်းအရင်းအမြစ်များကို ရှာဖွေပါ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **AI in Business** ကို အသုံးပြုခြင်းဆိုင်ရာ စီးပွားရေးအခန်းကဏ္ဍများ။ [AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) သင်ခန်းစာကို Microsoft Learn တွင် လေ့လာပါ။
* **AI in Business** ကို အသုံးချခြင်းဆိုင်ရာ စီးပွားရေးအခွင့်အလမ်းများ။ [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) သင်ခန်းစာလမ်းကြောင်းကို Microsoft Learn တွင် လေ့လာပါ။
* **Classic Machine Learning** ကို [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners) တွင် ရှင်းလင်းထားသည်။
* **Cognitive Services** အသုံးပြု၍ AI အလေ့အကျင့်များကို ဖန်တီးခြင်း။
* **Cloud Frameworks** အထူးသဖြင့် [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum) နှင့် [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) စသည်တို့ကို လေ့လာပါ။
* **Conversational AI** နှင့် **Chat Bots** ကို [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) သင်ခန်းစာတွင် လေ့လာပါ။
* **Deep Mathematics** ကို [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) စာအုပ်မှ လေ့လာပါ။
* **Cognitive Services** အသုံးပြု၍ AI လက်တွေ့အသုံးချမှုများ။ [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum) နှင့် [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum) သင်ခန်းစာများကို စတင်ပါ။
* **Cloud Frameworks** အထူးသဖြင့် [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum) နှင့် [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) ကို လေ့လာပါ။
* **Conversational AI** နှင့် **Chat Bots** ကို [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) သင်ခန်းစာလမ်းကြောင်းတွင် ရှာဖွေပါ။
* **Deep Mathematics** ကို [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) စာအုပ်မှ ရှင်းလင်းထားသည်။
AI in the Cloud အပေါ် အနည်းငယ်သော အကျဉ်းချုပ်ကို [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) သင်ခန်းစာမှ စတင်ပါ။
AI in the Cloud အပေါ် အခြေခံအဆင့်ကို [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) သင်ခန်းစာလမ်းကြောင်းတွင် လေ့လာပါ။
# အကြောင်းအရာ
| | သင်ခန်းစာလင့်ခ် | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [သင်ခန်းစာ Setup](./lessons/0-course-setup/setup.md) | [သင့် Development Environment ကို Setup လုပ်ပါ](./lessons/0-course-setup/how-to-run.md) | |
| 0 | [သင်ခန်းစာ Setup](./lessons/0-course-setup/setup.md) | [သင့် Development Environment ကို Setup ပြုလုပ်ပါ](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI အကျဉ်းချုပ်**](./lessons/1-Intro/README.md) | | |
| 01 | [AI အကျဉ်းချုပ်နှင့် သမိုင်း](./lessons/1-Intro/README.md) | - | - |
| 01 | [AI ၏ သမိုင်းနှင့် အကျဉ်းချုပ်](./lessons/1-Intro/README.md) | - | - |
| II | **Symbolic AI** |
| 02 | [Knowledge Representation နှင့် Expert Systems](./lessons/2-Symbolic/README.md) | [Expert Systems](./lessons/2-Symbolic/Animals.ipynb) / [Ontology](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Concept Graph](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Neural Networks အကျဉ်းချုပ်**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Multi-Layered Perceptron နှင့် ကိုယ်ပိုင် Framework ဖန်တီးခြင်း](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 04 | [Multi-Layered Perceptron နှင့် ကိုယ်ပိုင် Framework တည်ဆောက်ခြင်း](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Frameworks (PyTorch/TensorFlow) နှင့် Overfitting အကြောင်းမိတ်ဆက်](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**ကွန်ပျူတာမြင်ကွင်း (Computer Vision)**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure တွင် Computer Vision ကိုလေ့လာပါ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| IV | [**Computer Vision**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure တွင် Computer Vision ကိုလေ့လာပါ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Computer Vision အကြောင်းမိတ်ဆက်။ OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Convolutional Neural Networks](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN Architectures](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Pre-trained Networks နှင့် Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) and [Training Tricks](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
@ -85,58 +85,57 @@ AI in the Cloud အပေါ် အနည်းငယ်သော အကျဉ
| 10 | [Generative Adversarial Networks & Artistic Style Transfer](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Object Detection](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantic Segmentation. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**ဘာသာစကားအပြုအမူဆိုင်ရာ (Natural Language Processing)**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure တွင် Natural Language Processing ကိုလေ့လာပါ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [စာသားကိုယ်စားပြုမှု။ Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantic word embeddings. Word2Vec နှင့် GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [ဘာသာစကားမော်ဒယ်။ ကိုယ်ပိုင် embeddings များကိုလေ့ကျင့်ခြင်း](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [အကြီးစားဘာသာစကားမော်ဒယ်များ၊ Prompt Programming နှင့် Few-Shot Tasks](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure တွင် Natural Language Processing ကိုလေ့လာပါ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Text Representation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantic word embeddings. Word2Vec နှင့် GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Language Modeling. သင့်ကိုယ်ပိုင် embeddings ကို Training လုပ်ခြင်း](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Large Language Models, Prompt Programming နှင့် Few-Shot Tasks](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **အခြား AI နည်းလမ်းများ** || |
| 21 | [Genetic Algorithms](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Deep Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Multi-Agent Systems](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI ကျင့်ဝတ်သိက္ခာများ** | | |
| 24 | [AI ကျင့်ဝတ်သိက္ခာနှင့် တာဝန်ရှိသော AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Responsible AI Principles](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **အပိုဆောင်းများ** | | |
| VII | **AI Ethics** | | |
| 24 | [AI Ethics နှင့် တာဝန်ရှိသော AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Responsible AI Principles](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **အပိုများ** | | |
| 25 | [Multi-Modal Networks, CLIP နှင့် VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## သင်ခန်းစာတိုင်းတွင် ပါဝင်သည်
## သင်ခန်းစာတစ်ခုစီတွင် ပါဝင်သည်
* ကြိုတင်ဖတ်ရှုရန်အကြောင်းအရာများ
* **PyTorch** သို့မဟုတ် **TensorFlow** framework အတွက် သီးသန့်ရေးသားထားသော Jupyter Notebooks များ။ ဤ notebooks များတွင် သီအိုရီဆိုင်ရာအကြောင်းအရာများလည်း ပါဝင်ပြီး သင်ခန်းစာကို နားလည်ရန်အတွက် PyTorch သို့မဟုတ် TensorFlow ၏ အနည်းဆုံးတစ်မျိုးကို လေ့လာရန်လိုအပ်ပါသည်။
* **Labs** သင်ခန်းစာအချို့တွင် ရရှိနိုင်ပြီး သင်လေ့လာထားသောအကြောင်းအရာများကို သတ်မှတ်ပြဿနာတစ်ခုတွင် လက်တွေ့ကျင့်သုံးနိုင်စေရန် အခွင့်အရေးပေးပါသည်။
* အချို့သောအပိုင်းများတွင် [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) ၏ ဆက်စပ်အကြောင်းအရာများကို လင့်ခ်များဖြင့် ပံ့ပိုးထားပါသည်။
* ကြိုတင်ဖတ်ရှုရန်အကြောင်းအရာများ
* Framework (**PyTorch** သို့မဟုတ် **TensorFlow**) အတွက် သီးသန့်ဖြစ်သော Jupyter Notebooks များ။ Notebook တွင် သီအိုရီအကြောင်းအရာများစွာပါဝင်ပြီး၊ အကြောင်းအရာကို နားလည်ရန်အတွက် Notebook တစ်ခု (PyTorch သို့မဟုတ် TensorFlow) ကို အနည်းဆုံး လေ့လာရပါမည်။
* **Labs** သင်ခန်းစာတစ်ချို့တွင် ရရှိနိုင်ပြီး သင်လေ့လာထားသော အကြောင်းအရာကို သတ်မှတ်ထားသော ပြဿနာတစ်ခုတွင် အသုံးချရန် အခွင့်အရေးပေးသည်။
* အချို့သော အပိုင်းများတွင် [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) မှ ဆက်စပ်အကြောင်းအရာများကို လင့်ခ်များဖြင့် ဖော်ပြထားသည်။
## စတင်ရန်
- သင်၏ ဖွံ့ဖြိုးရေးပတ်ဝန်းကျင်ကို ပြင်ဆင်ရန်အတွက် [setup lesson](./lessons/0-course-setup/setup.md) ကို ဖန်တီးထားပါသည်။
- ဆရာများအတွက်လည်း [curricula setup lesson](./lessons/0-course-setup/for-teachers.md) ကို ဖန်တီးထားပါသည်။
- [VSCode သို့မဟုတ် Codepace တွင် ကုဒ်ကို အလုပ်လုပ်စေခြင်း](./lessons/0-course-setup/how-to-run.md) အကြောင်းကိုလည်း ဖတ်ရှုနိုင်ပါသည်။
- သင်၏ Development Environment ကို စတင်တည်ဆောက်ရန်အတွက် [setup lesson](./lessons/0-course-setup/setup.md) ကို ဖန်တီးထားပါသည်။ - သင်တန်းပို့ချသူများအတွက် [curricula setup lesson](./lessons/0-course-setup/for-teachers.md) ကိုလည်း ဖန်တီးထားပါသည်။
- [VSCode သို့မဟုတ် Codepace တွင် ကုဒ်ကို အလုပ်လုပ်ရန်](./lessons/0-course-setup/how-to-run.md) နည်းလမ်းကို လေ့လာပါ။
ဤအဆင့်များကို လိုက်နာပါ-
အောက်ပါအဆင့်များကို လိုက်နာပါ-
Repository ကို Fork လုပ်ပါ- ဤစာမျက်နှာ၏ အပေါ်ညာဘက်ထောင့်ရှိ "Fork" ခလုတ်ကို နှိပ်ပါ။
Repository ကို Fork လုပ်ပါ- ဒီစာမျက်နှာ၏ အပေါ်ယာဉ်ဘက်ရှိ "Fork" ခလုတ်ကို နှိပ်ပါ။
Repository ကို Clone လုပ်ပါ- `git clone https://github.com/microsoft/AI-For-Beginners.git`
ဤ repo ကို နောက်ပိုင်းတွင် လွယ်ကူစွာ ရှာဖွေရန်အတွက် star (🌟) လုပ်ထားပါ။
ဒီ Repo ကို နောက်မှ လွယ်ကူစွာ ရှာဖွေရန်အတွက် 🌟 (Star) လုပ်ရန် မမေ့ပါနှင့်။
## အခြားသင်ကြားသူများနှင့်တွေ့ဆုံပါ
## အခြားလေ့လာသူများနှင့် တွေ့ဆုံပါ
ဤသင်တန်းကို လေ့လာနေသော အခြားသင်ကြားသူများနှင့် တွေ့ဆုံရန်နှင့် အထောက်အပံ့ရရန် [AI Discord server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) တွင် ပါဝင်ပါ။
ဒီသင်ခန်းစာကို လေ့လာနေသော အခြားလေ့လာသူများနှင့် တွေ့ဆုံရန်နှင့် အထောက်အပံ့ရရန် [AI Discord server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) ကို Join လုပ်ပါ။
သင်တစ်စုံတစ်ရာ ဖန်တီးနေစဉ်တွင် ထုတ်ကုန်အကြံပြုချက်များ သို့မဟုတ် မေးခွန်းများရှိပါက [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) သို့ သွားပါ။
သင်တည်ဆောက်နေစဉ်တွင် ထုတ်ကုန်အကြောင်းအရာ သို့မဟုတ် မေးခွန်းများရှိပါက [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) ကို သွားရောက်ပါ။
## စစ်ဆေးမေးခွန်းများ
> **မေးခွန်းများအကြောင်းမှတ်ချက်**: မေးခွန်းများအားလုံးသည် Quiz-app ဖိုလ်ဒါတွင် etc\quiz-app တွင်ပါရှိပြီး၊ [အွန်လိုင်းတွင် ဒီမှာ](https://ff-quizzes.netlify.app/) တွေ့နိုင်ပါသည်။ မေးခွန်းများကို သင်ခန်းစာများအတွင်းမှ ချိတ်ဆက်ထားပြီး၊ quiz app ကို ဒေသတွင်းတွင် အလုပ်လည်စေခြင်း သို့မဟုတ် Azure တွင် တင်သွင်းနိုင်ပါသည်။ `quiz-app` ဖိုလ်ဒါအတွင်းရှိ လမ်းညွှန်ချက်များကို လိုက်နာပါ။ မေးခွန်းများကို တဖြည်းဖြည်း ဒေသိယပြုလုပ်နေပါသည်။
## Quizများ
> **မေးခွန်းများအကြောင်းမှတ်ချက်**: မေးခွန်းများအားလုံးကို Quiz-app ဖိုလ်ဒါထဲရှိ etc\quiz-app တွင်ထားရှိထားပြီး [အွန်လိုင်းတွင်](https://ff-quizzes.netlify.app/) တွေ့နိုင်ပါသည်။ မေးခွန်းများကို သင်ခန်းစာများအတွင်းမှချိတ်ဆက်ထားပြီး quiz app ကို ဒေသတွင်းတွင် run လုပ်နိုင်သလို Azure တွင် deploy လုပ်နိုင်ပါသည်။ `quiz-app` ဖိုလ်ဒါထဲရှိလမ်းညွှန်ချက်များကိုလိုက်နာပါ။ မေးခွန်းများကို တဖြည်းဖြည်း ဒေသခံအဖြစ်ပြောင်းလဲနေပါသည်။
## အကူအညီလိုအပ်သည်
သင်မှာ အကြံပြုချက်များရှိပါသလား၊ ဒါမှမဟုတ် စာလုံးပေါင်းအမှားများ သို့မဟုတ် ကုဒ်အမှားများ ရှာဖွေတွေ့ရှိပါသလား။ Issue တစ်ခုတင်ပါ သို့မဟုတ် Pull Request တစ်ခု ဖန်တီးပါ။
အကြံပြုချက်များရှိပါသလား၊ သို့မဟုတ် စာလုံးပေါင်းအမှားများ၊ ကုဒ်အမှားများကို ရှာဖွေတွေ့ရှိပါသလား။ Issue တစ်ခုတင်ပါ၊ သို့မဟုတ် Pull Request တစ်ခုဖန်တီးပါ။
## အထူးကျေးဇူးတင်ပါသည်
## အထူးကျေးဇူးတင်ရှိမှု
* **✍️ အဓိကရေးသားသူ:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 တည်းဖြတ်သူ:** [Jen Looper](https://twitter.com/jenlooper), PhD
@ -146,7 +145,7 @@ Repository ကို Clone လုပ်ပါ- `git clone https://github.com/mic
## အခြားသင်ခန်းစာများ
ကျွန်ုပ်တို့၏အဖွဲ့သည် အခြားသင်ခန်းစာများကိုလည်း ထုတ်လုပ်ပါသည်။ စစ်ဆေးကြည့်ပါ-
ကျွန်ုပ်တို့၏အဖွဲ့သည် အခြားသင်ခန်းစာများကိုလည်း ထုတ်လုပ်ပါသည်။ ကြည့်ရှုပါ:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
@ -166,4 +165,4 @@ Repository ကို Clone လုပ်ပါ- `git clone https://github.com/mic
---
**အကြောင်းကြားချက်**:
ဤစာရွက်စာတမ်းကို AI ဘာသာပြန်ဝန်ဆောင်မှု [Co-op Translator](https://github.com/Azure/co-op-translator) ကို အသုံးပြု၍ ဘာသာပြန်ထားပါသည်။ ကျွန်ုပ်တို့သည် တိကျမှုအတွက် ကြိုးစားနေသော်လည်း၊ အလိုအလျောက် ဘာသာပြန်ခြင်းတွင် အမှားများ သို့မဟုတ် မမှန်ကန်မှုများ ပါရှိနိုင်သည်ကို သတိပြုပါ။ မူရင်းဘာသာစကားဖြင့် ရေးသားထားသော စာရွက်စာတမ်းကို အာဏာတရားရှိသော ရင်းမြစ်အဖြစ် သတ်မှတ်သင့်ပါသည်။ အရေးကြီးသော အချက်အလက်များအတွက် လူ့ဘာသာပြန်ပညာရှင်များမှ ပရော်ဖက်ရှင်နယ် ဘာသာပြန်ခြင်းကို အကြံပြုပါသည်။ ဤဘာသာပြန်ကို အသုံးပြုခြင်းမှ ဖြစ်ပေါ်လာသော အလွဲအလွတ်များ သို့မဟုတ် အနားယူမှားမှုများအတွက် ကျွန်ုပ်တို့သည် တာဝန်မယူပါ။
ဤစာရွက်စာတမ်းကို AI ဘာသာပြန်ဝန်ဆောင်မှု [Co-op Translator](https://github.com/Azure/co-op-translator) ကို အသုံးပြု၍ ဘာသာပြန်ထားပါသည်။ ကျွန်ုပ်တို့သည် တိကျမှုအတွက် ကြိုးစားနေသော်လည်း၊ အလိုအလျောက် ဘာသာပြန်ခြင်းတွင် အမှားများ သို့မဟုတ် မတိကျမှုများ ပါရှိနိုင်သည်ကို သတိပြုပါ။ မူရင်းဘာသာစကားဖြင့် ရေးသားထားသော စာရွက်စာတမ်းကို အာဏာရှိသော ရင်းမြစ်အဖြစ် သတ်မှတ်သင့်ပါသည်။ အရေးကြီးသော အချက်အလက်များအတွက် လူ့ဘာသာပြန်ပညာရှင်များမှ ပရော်ဖက်ရှင်နယ် ဘာသာပြန်ခြင်းကို အကြံပြုပါသည်။ ဤဘာသာပြန်ကို အသုံးပြုခြင်းမှ ဖြစ်ပေါ်လာသော အလွဲအလွဲအချော်များ သို့မဟုတ် အနားလွဲမှုများအတွက် ကျွန်ုပ်တို့သည် တာဝန်မယူပါ။

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@ -1,8 +1,8 @@
<!--
CO_OP_TRANSLATOR_METADATA:
{
"original_hash": "07191303b7ea2aff1d47e2b0fe4bb862",
"translation_date": "2025-08-29T06:47:46+00:00",
"original_hash": "2c8099af824bae942ca6ea7e53284770",
"translation_date": "2025-09-07T13:41:54+00:00",
"source_file": "README.md",
"language_code": "ne"
}
@ -21,79 +21,79 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# सुरुवातीका लागि कृत्रिम बुद्धिमत्ता - एक पाठ्यक्रम
# सुरुवातका लागि कृत्रिम बुद्धिमत्ता - एक पाठ्यक्रम
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.ne.png)|
|:---:|
| सुरुवातीका लागि AI - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ |
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.ne.png)|
|:---:|
| सुरुवातका लागि AI - _[@girlie_mac](https://twitter.com/girlie_mac) द्वारा स्केच नोट_ |
**कृत्रिम बुद्धिमत्ता** (AI) को संसार अन्वेषण गर्नुहोस् हाम्रो १२ हप्ताको, २४ पाठको पाठ्यक्रमसँग! यसमा व्यावहारिक पाठहरू, क्विजहरू, र प्रयोगशालाहरू समावेश छन्। पाठ्यक्रम सुरुवातीका लागि उपयुक्त छ र TensorFlow र PyTorch जस्ता उपकरणहरू, साथै AI मा नैतिकता समेट्छ।
**कृत्रिम बुद्धिमत्ता** (AI) को संसारमा हाम्रो १२-हप्ताको, २४-पाठको पाठ्यक्रमसँग अन्वेषण गर्नुहोस्! यसमा व्यावहारिक पाठहरू, प्रश्नोत्तर, र प्रयोगशालाहरू समावेश छन्। यो पाठ्यक्रम सुरुवातकर्ताहरूका लागि उपयुक्त छ र TensorFlow र PyTorch जस्ता उपकरणहरू, साथै AI मा नैतिकता समेट्छ।
### 🌐 बहुभाषी समर्थन
### 🌐 बहुभाषिक समर्थन
#### GitHub Action मार्फत समर्थित (स्वचालित र सधैं अद्यावधिक)
#### GitHub Action मार्फत समर्थित (स्वचालित र सधैं अद्यावधिक)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](./README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**यदि तपाईं थप भाषाहरूको अनुवाद चाहनुहुन्छ भने यहाँ सूचीबद्ध छन् [यहाँ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**यदि तपाईं थप भाषाहरूको अनुवाद चाहनुहुन्छ भने, समर्थित भाषाहरूको सूची [यहाँ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) हेर्नुहोस्।**
## समुदायमा सामेल हुनुहोस्
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## तपाईंले के सिक्नुहुनेछ
**[पाठ्यक्रमको मनम्याप](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[पाठ्यक्रमको माईन्डम्याप](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
यस पाठ्यक्रममा, तपाईंले सिक्नुहुनेछ:
* कृत्रिम बुद्धिमत्ताका विभिन्न दृष्टिकोणहरू, जसमा "पुरानो राम्रो" प्रतीकात्मक दृष्टिकोण **ज्ञान प्रतिनिधित्व** र तर्क ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)) समावेश छ।
* **न्यूरल नेटवर्कहरू** र **डीप लर्निङ**, जुन आधुनिक AI को केन्द्रमा छन्। हामी यी महत्त्वपूर्ण विषयहरूको अवधारणालाई दुई लोकप्रिय फ्रेमवर्कहरू - [TensorFlow](http://Tensorflow.org) र [PyTorch](http://pytorch.org) को कोड प्रयोग गरेर चित्रण गर्नेछौं।
* छविहरू र पाठसँग काम गर्नका लागि **न्यूरल आर्किटेक्चरहरू**। हामी हालका मोडेलहरू समेट्नेछौं तर अत्याधुनिकमा केही कमी हुन सक्छ।
* कृत्रिम बुद्धिमत्ताका विभिन्न दृष्टिकोणहरू, जस्तै "पुरानो" प्रतीकात्मक दृष्टिकोण **ज्ञान प्रतिनिधित्व** र तर्कसहित ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))।
* **न्यूरल नेटवर्कहरू** र **डिप लर्निङ**, जुन आधुनिक AI को केन्द्रमा छन्। यी महत्त्वपूर्ण विषयहरूको अवधारणाहरू दुई लोकप्रिय फ्रेमवर्कहरू - [TensorFlow](http://Tensorflow.org) र [PyTorch](http://pytorch.org) को कोड प्रयोग गरेर व्याख्या गरिनेछ।
* छविहरू र पाठसँग काम गर्नका लागि **न्यूरल आर्किटेक्चरहरू**। हामी हालका मोडेलहरू समेट्नेछौं तर अत्याधुनिक मोडेलहरूमा केही कमी हुन सक्छ।
* कम लोकप्रिय AI दृष्टिकोणहरू, जस्तै **जेनेटिक एल्गोरिदमहरू** र **मल्टि-एजेन्ट सिस्टमहरू**।
हामीले यस पाठ्यक्रममा समेट्ने छैनौं:
यो पाठ्यक्रममा हामीले समेट्ने छैनौं:
> [यस पाठ्यक्रमका सबै अतिरिक्त स्रोतहरू हाम्रो Microsoft Learn संग्रहमा फेला पार्नुहोस्](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **व्यवसायमा AI को प्रयोग** को व्यापारिक केसहरू। [व्यवसाय प्रयोगकर्ताहरूका लागि AI को परिचय](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) सिक्ने मार्ग Microsoft Learn मा लिनुहोस्, वा [AI व्यवसाय स्कूल](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), [INSEAD](https://www.insead.edu/) सँग सहकार्यमा विकसित।
* **क्लासिक मेसिन लर्निङ**, जुन हाम्रो [सुरुवातीका लागि मेसिन लर्निङ पाठ्यक्रम](http://github.com/Microsoft/ML-for-Beginners) मा राम्रोसँग वर्णन गरिएको छ।
* **[कग्निटिभ सर्भिसहरू](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** प्रयोग गरेर व्यावहारिक AI अनुप्रयोगहरू। यसका लागि, हामी तपाईंलाई Microsoft Learn मा [दृष्टि](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [प्राकृतिक भाषा प्रशोधन](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI सेवा प्रयोग गरेर जेनेरेटिभ AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** र अन्यका लागि मोड्युलहरू सुरु गर्न सिफारिस गर्छौं।
* **विशिष्ट मेसिन लर्निङ क्लाउड फ्रेमवर्कहरू**, जस्तै [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), वा [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)। [Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) र [Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) सिक्ने मार्गहरू प्रयोग गर्न विचार गर्नुहोस्।
* **संवादात्मक AI** र **च्याट बोटहरू**। त्यहाँ छुट्टै [संवादात्मक AI समाधानहरू सिर्जना गर्नुहोस्](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) सिक्ने मार्ग छ, र तपाईं [यो ब्लग पोस्ट](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) मा थप विवरणका लागि सन्दर्भ गर्न सक्नुहुन्छ।
* **डीप लर्निङको गहिरो गणित**। यसका लागि, हामी [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) Ian Goodfellow, Yoshua Bengio र Aaron Courville द्वारा सिफारिस गर्छौं, जुन [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) मा अनलाइन उपलब्ध छ।
* **व्यवसायमा AI को प्रयोग**। [व्यवसाय प्रयोगकर्ताहरूका लागि AI को परिचय](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) सिकाइ मार्ग लिनुहोस्, वा [AI व्यवसाय स्कूल](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), जुन [INSEAD](https://www.insead.edu/) सँगको सहकार्यमा विकास गरिएको हो।
* **क्लासिक मेसिन लर्निङ**, जुन हाम्रो [सुरुवातकर्ताहरूका लागि मेसिन लर्निङ पाठ्यक्रम](http://github.com/Microsoft/ML-for-Beginners) मा राम्रोसँग वर्णन गरिएको छ।
* **[कग्निटिभ सर्भिसहरू](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** प्रयोग गरेर बनाइएका व्यावहारिक AI अनुप्रयोगहरू। यसका लागि, [दृष्टि](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [प्राकृतिक भाषा प्रशोधन](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI सेवा](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** र अन्यका लागि Microsoft Learn मा सुरु गर्नुहोस्।
* विशिष्ट ML **क्लाउड फ्रेमवर्कहरू**, जस्तै [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), वा [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)। [Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) र [Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) सिकाइ मार्गहरू प्रयोग गर्नुहोस्।
* **संवादात्मक AI** र **च्याट बटहरू**। [संवादात्मक AI समाधानहरू सिर्जना गर्नुहोस्](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) सिकाइ मार्ग लिनुहोस्, र थप विवरणका लागि [यो ब्लग पोस्ट](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) हेर्नुहोस्।
* **डिप लर्निङको गहिरो गणित**। यसका लागि, हामी [डिप लर्निङ](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) पुस्तक सिफारिस गर्छौं, जसलाई [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) मा अनलाइन पनि उपलब्ध छ।
क्लाउडमा _AI_ को कोमल परिचयका लागि तपाईं [Azure मा कृत्रिम बुद्धिमत्तासँग सुरु गर्नुहोस्](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) सिक्ने मार्ग लिन विचार गर्न सक्नुहुन्छ।
_क्लाउडमा AI_ को कोमल परिचयका लागि, [Azure मा कृत्रिम बुद्धिमत्तासँग सुरु गर्नुहोस्](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) सिकाइ मार्ग लिनुहोस्।
# सामग्री
| | पाठ लिंक | PyTorch/Keras/TensorFlow | प्रयोगशाला |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [पाठ्यक्रम सेटअप](./lessons/0-course-setup/setup.md) | [तपाईंको विकास वातावरण सेटअप गर्नुहोस्](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI को परिचय**](./lessons/1-Intro/README.md) | | |
| 01 | [AI को परिचय र इतिहास](./lessons/1-Intro/README.md) | - | - |
| II | **प्रतीकात्मक AI** |
| 02 | [ज्ञान प्रतिनिधित्व र विशेषज्ञ प्रणालीहरू](./lessons/2-Symbolic/README.md) | [विशेषज्ञ प्रणालीहरू](./lessons/2-Symbolic/Animals.ipynb) / [Ontology](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Concept Graph](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**न्यूरल नेटवर्कहरूको परिचय**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [मल्टि-लेयर्ड Perceptron र हाम्रो आफ्नै फ्रेमवर्क सिर्जना गर्दै](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| | पाठ लिंक | PyTorch/Keras/TensorFlow | प्रयोगशाला |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [पाठ्यक्रम सेटअप](./lessons/0-course-setup/setup.md) | [तपाईंको विकास वातावरण सेटअप गर्नुहोस्](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI को परिचय**](./lessons/1-Intro/README.md) | | |
| 01 | [AI को परिचय र इतिहास](./lessons/1-Intro/README.md) | - | - |
| II | **प्रतीकात्मक AI** |
| 02 | [ज्ञान प्रतिनिधित्व र विशेषज्ञ प्रणालीहरू](./lessons/2-Symbolic/README.md) | [विशेषज्ञ प्रणालीहरू](./lessons/2-Symbolic/Animals.ipynb) / [ओन्टोलोजी](./lessons/2-Symbolic/FamilyOntology.ipynb) /[अवधारणा ग्राफ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**न्यूरल नेटवर्कहरूको परिचय**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [परसेप्ट्रोन](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [नोटबुक](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [प्रयोगशाला](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [बहु-स्तरीय परसेप्ट्रोन र हाम्रो आफ्नै फ्रेमवर्क सिर्जना गर्नुहोस्](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [नोटबुक](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [प्रयोगशाला](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [फ्रेमवर्क्स (PyTorch/TensorFlow) र ओभरफिटिङको परिचय](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [प्रयोगशाला](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**कम्प्युटर भिजन**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure मा कम्प्युटर भिजन अन्वेषण गर्नुहोस्](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [कम्प्युटर भिजनको परिचय। OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [नोटबुक](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [प्रयोगशाला](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [कन्भोलुसनल न्युरल नेटवर्कहरू](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN आर्किटेक्चरहरू](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [प्रयोगशाला](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [पूर्व-प्रशिक्षित नेटवर्कहरू र ट्रान्सफर लर्निङ](./lessons/4-ComputerVision/08-TransferLearning/README.md) र [प्रशिक्षणका तरिकाहरू](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [प्रयोगशाला](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [अटोइन्कोडरहरू र VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [जेनेरेटिभ एड्भर्सेरियल नेटवर्कहरू र कलात्मक शैली ट्रान्सफर](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 09 | [अटोएनकोडरहरू र VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [जेनेरेटिभ एडभर्सेरियल नेटवर्कहरू र कलात्मक शैली ट्रान्सफर](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [वस्तु पहिचान](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [प्रयोगशाला](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [सिमान्टिक सेग्मेन्टेसन। U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| 12 | [सामान्य खण्डीकरण। U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**प्राकृतिक भाषा प्रशोधन**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure मा प्राकृतिक भाषा प्रशोधन अन्वेषण गर्नुहोस्](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [पाठ प्रतिनिधित्व। Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [सिमान्टिक शब्द एम्बेडिङहरू। Word2Vec र GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [भाषा मोडलिङ। आफ्नै एम्बेडिङहरू प्रशिक्षण गर्नुहोस्](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [प्रयोगशाला](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [पुनरावर्ती न्युरल नेटवर्कहरू](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [जेनेरेटिभ पुनरावर्ती नेटवर्कहरू](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [प्रयोगशाला](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ट्रान्सफर्मरहरू। BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [नामित इकाई पहिचान](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [प्रयोगशाला](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [ठूलो भाषा मोडलहरू, प्रम्प्ट प्रोग्रामिङ र थोरै-शट कार्यहरू](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [पाठ प्रतिनिधित्व। Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [सामान्य शब्द एम्बेडिङहरू। Word2Vec र GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [भाषा मोडलिङ। आफ्नै एम्बेडिङहरू प्रशिक्षण गर्नुहोस्](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [प्रयोगशाला](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [पुनरावर्ती न्युरल नेटवर्कहरू](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [जेनेरेटिभ पुनरावर्ती नेटवर्कहरू](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [प्रयोगशाला](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ट्रान्सफर्मरहरू। BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [नामित इकाई पहिचान](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [प्रयोगशाला](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [ठूलो भाषा मोडलहरू, प्रम्प्ट प्रोग्रामिङ र थोरै-शट कार्यहरू](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **अन्य AI प्रविधिहरू** || |
| 21 | [जेनेटिक एल्गोरिदमहरू](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [नोटबुक](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [डीप रिइन्फोर्समेन्ट लर्निङ](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [प्रयोगशाला](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -106,8 +106,8 @@ CO_OP_TRANSLATOR_METADATA:
## प्रत्येक पाठमा समावेश छ
* पूर्व-पढाइ सामग्री
* कार्यान्वयन योग्य Jupyter नोटबुकहरू, जुन प्रायः फ्रेमवर्क (**PyTorch** वा **TensorFlow**) का लागि विशिष्ट हुन्छन्। कार्यान्वयन योग्य नोटबुकमा धेरै सैद्धान्तिक सामग्री पनि समावेश छ, त्यसैले विषयलाई बुझ्नको लागि तपाईंले कम्तीमा एउटा संस्करणको नोटबुक (PyTorch वा TensorFlow) हेर्नुपर्छ।
* **प्रयोगशालाहरू** केही विषयहरूको लागि उपलब्ध छन्, जसले तपाईंलाई सिकेको सामग्रीलाई विशेष समस्यामा लागू गर्ने अवसर दिन्छ।
* कार्यान्वयन योग्य Jupyter नोटबुकहरू, जुन प्रायः फ्रेमवर्क (**PyTorch** वा **TensorFlow**) का लागि विशिष्ट हुन्छन्। कार्यान्वयन योग्य नोटबुकमा धेरै सैद्धान्तिक सामग्री पनि समावेश छ, त्यसैले विषयलाई बुझ्नको लागि तपाईंले कम्तीमा एउटा संस्करण (PyTorch वा TensorFlow) नोटबुक हेर्नु आवश्यक छ।
* **प्रयोगशाला** केही विषयहरूका लागि उपलब्ध छन्, जसले तपाईंलाई सिकेको सामग्रीलाई विशेष समस्यामा लागू गर्ने अवसर दिन्छ।
* केही खण्डहरूमा [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) मा सम्बन्धित विषयहरू समेट्ने लिंकहरू समावेश छन्।
## सुरु गर्दै
@ -123,22 +123,22 @@ CO_OP_TRANSLATOR_METADATA:
यो रेपो पछि सजिलै फेला पार्नको लागि स्टार (🌟) गर्न नबिर्सनुहोस्।
## अन्य सिक्नेहरूसँग भेट्नुहोस्
## अन्य सिक्नेहरूलाई भेट्नुहोस्
हाम्रो [औपचारिक AI Discord सर्भर](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) मा सामेल हुनुहोस् ताकि यस कोर्स लिने अन्य सिक्नेहरूसँग भेटघाट र नेटवर्क गर्न सक्नुहोस् र सहयोग प्राप्त गर्न सक्नुहोस्।
यदि तपाईंलाई उत्पादन प्रतिक्रिया वा निर्माण गर्दा प्रश्नहरू छन् भने हाम्रो [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) मा जानुहोस्।
## क्विजहरू
> **क्विजहरूको बारेमा नोट**: सबै क्विजहरू `Quiz-app` फोल्डरमा etc\quiz-app मा समावेश छन्, वा [अनलाइन यहाँ](https://ff-quizzes.netlify.app/) उपलब्ध छन्। ती पाठहरूबाट लिंक गरिएको छ। `quiz-app` स्थानीय रूपमा चलाउन सकिन्छ वा Azure मा डिप्लोय गर्न सकिन्छ; `quiz-app` फोल्डरमा दिइएको निर्देशनहरू पालना गर्नुहोस्। ती क्रमिक रूपमा स्थानीयकरण गरिँदैछन्।
## सहयोग चाहिएको छ
> **क्विजहरूको बारेमा नोट**: सबै क्विजहरू `Quiz-app` फोल्डरमा `etc\quiz-app` मा समावेश छन्, वा [अनलाइन यहाँ](https://ff-quizzes.netlify.app/) उपलब्ध छन्। ती पाठहरूभित्र लिंक गरिएको छ। `quiz-app` स्थानीय रूपमा चलाउन सकिन्छ वा Azure मा डिप्लोय गर्न सकिन्छ; `quiz-app` फोल्डरमा दिइएको निर्देशनहरू पालना गर्नुहोस्। ती क्रमिक रूपमा स्थानीयकरण गरिँदैछन्।
## सहयोग आवश्यक
के तपाईंसँग सुझावहरू छन् वा कुनै हिज्जे वा कोड त्रुटि फेला पार्नुभएको छ? कृपया एउटा मुद्दा उठाउनुहोस् वा पुल अनुरोध सिर्जना गर्नुहोस्।
के तपाईंसँग सुझावहरू छन् वा कुनै हिज्जे वा कोड त्रुटि फेला पार्नुभएको छ? कृपया एउटा मुद्दा उठाउनुहोस् वा एउटा पुल अनुरोध सिर्जना गर्नुहोस्।
## विशेष धन्यवाद
* **✍️ मुख्य लेखक:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 सम्पादक:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **✍️ मुख्य लेखक:** [Dmitry Soshnikov](http://soshnikov.com), पीएचडी
* **🔥 सम्पादक:** [Jen Looper](https://twitter.com/jenlooper), पीएचडी
* **🎨 स्केच नोट चित्रकार:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ क्विज सिर्जनाकर्ता:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 मुख्य योगदानकर्ता:** [Evgenii Pishchik](https://github.com/Pe4enIks)
@ -165,4 +165,4 @@ CO_OP_TRANSLATOR_METADATA:
---
**अस्वीकरण**:
यो दस्तावेज़ AI अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) प्रयोग गरेर अनुवाद गरिएको छ। हामी शुद्धताको लागि प्रयास गर्छौं, तर कृपया ध्यान दिनुहोस् कि स्वचालित अनुवादमा त्रुटिहरू वा अशुद्धताहरू हुन सक्छ। यसको मूल भाषा मा रहेको मूल दस्तावेज़लाई आधिकारिक स्रोत मानिनुपर्छ। महत्वपूर्ण जानकारीको लागि, व्यावसायिक मानव अनुवाद सिफारिस गरिन्छ। यस अनुवादको प्रयोगबाट उत्पन्न हुने कुनै पनि गलतफहमी वा गलत व्याख्याको लागि हामी जिम्मेवार हुने छैनौं।
यो दस्तावेज़ AI अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) प्रयोग गरेर अनुवाद गरिएको छ। हामी शुद्धताको लागि प्रयास गर्छौं, तर कृपया ध्यान दिनुहोस् कि स्वचालित अनुवादहरूमा त्रुटि वा अशुद्धता हुन सक्छ। यसको मूल भाषा मा रहेको मूल दस्तावेज़लाई आधिकारिक स्रोत मानिनुपर्छ। महत्वपूर्ण जानकारीको लागि, व्यावसायिक मानव अनुवाद सिफारिस गरिन्छ। यस अनुवादको प्रयोगबाट उत्पन्न हुने कुनै पनि गलतफहमी वा गलत व्याख्याको लागि हामी जिम्मेवार हुने छैनौं।

102
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@ -1,8 +1,8 @@
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@ -46,7 +46,7 @@ Ontdek de wereld van **Kunstmatige Intelligentie** (AI) met ons 12-weken durende
In dit curriculum leer je:
* Verschillende benaderingen van Kunstmatige Intelligentie, waaronder de "goede oude" symbolische benadering met **Kennisrepresentatie** en redeneren ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* Verschillende benaderingen van Kunstmatige Intelligentie, inclusief de "goede oude" symbolische benadering met **Kennisrepresentatie** en redeneren ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neurale Netwerken** en **Deep Learning**, die de kern vormen van moderne AI. We illustreren de concepten achter deze belangrijke onderwerpen met code in twee van de meest populaire frameworks - [TensorFlow](http://Tensorflow.org) en [PyTorch](http://pytorch.org).
* **Neurale Architecturen** voor het werken met afbeeldingen en tekst. We behandelen recente modellen, maar mogelijk niet de allernieuwste.
* Minder populaire AI-benaderingen, zoals **Genetische Algoritmen** en **Multi-Agent Systemen**.
@ -55,18 +55,18 @@ Wat we niet behandelen in dit curriculum:
> [Vind alle aanvullende bronnen voor deze cursus in onze Microsoft Learn-collectie](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Zakelijke toepassingen van **AI in Business**. Overweeg de leerroute [Introductie tot AI voor zakelijke gebruikers](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) op Microsoft Learn, of [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), ontwikkeld in samenwerking met [INSEAD](https://www.insead.edu/).
* Zakelijke toepassingen van **AI in Business**. Overweeg het volgen van [Introductie tot AI voor zakelijke gebruikers](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) leerpad op Microsoft Learn, of [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), ontwikkeld in samenwerking met [INSEAD](https://www.insead.edu/).
* **Klassieke Machine Learning**, die goed wordt beschreven in ons [Machine Learning voor Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners).
* Praktische AI-toepassingen gebouwd met **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Hiervoor raden we aan te beginnen met modules op Microsoft Learn voor [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generatieve AI met Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** en anderen.
* Specifieke ML **Cloud Frameworks**, zoals [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), of [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Overweeg de leerpaden [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) en [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Conversational AI** en **Chat Bots**. Er is een aparte leerroute [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), en je kunt ook verwijzen naar [deze blogpost](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) voor meer details.
* Specifieke ML **Cloud Frameworks**, zoals [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), of [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Overweeg het gebruik van [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) en [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) leerpaden.
* **Conversational AI** en **Chat Bots**. Er is een apart [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) leerpad, en je kunt ook verwijzen naar [deze blogpost](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) voor meer details.
* **Diepe Wiskunde** achter deep learning. Hiervoor raden we [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) aan door Ian Goodfellow, Yoshua Bengio en Aaron Courville, die ook online beschikbaar is op [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Voor een eenvoudige introductie tot _AI in de Cloud_ kun je overwegen de leerroute [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) te volgen.
Voor een zachte introductie tot _AI in de Cloud_ onderwerpen kun je overwegen het [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) leerpad te volgen.
# Inhoud
| | Les Link | PyTorch/Keras/TensorFlow | Lab |
| | Leslink | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Cursus Setup](./lessons/0-course-setup/setup.md) | [Setup Je Ontwikkelomgeving](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Introductie tot AI**](./lessons/1-Intro/README.md) | | |
@ -75,7 +75,7 @@ Voor een eenvoudige introductie tot _AI in de Cloud_ kun je overwegen de leerrou
| 02 | [Kennisrepresentatie en Expertsystemen](./lessons/2-Symbolic/README.md) | [Expertsystemen](./lessons/2-Symbolic/Animals.ipynb) / [Ontologie](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Concept Graph](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Introductie tot Neurale Netwerken**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Multi-Laags Perceptron en Ons Eigen Framework Maken](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 04 | [Multi-Layered Perceptron en Ons Eigen Framework Maken](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Introductie tot Frameworks (PyTorch/TensorFlow) en Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Computer Vision**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Ontdek Computer Vision op Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Introductie tot Computer Vision. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
@ -85,82 +85,82 @@ Voor een eenvoudige introductie tot _AI in de Cloud_ kun je overwegen de leerrou
| 10 | [Generatieve Adversariële Netwerken & Artistieke Stijltransfer](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Objectdetectie](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantische Segmentatie. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Ontdek Natural Language Processing op Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Tekstrepresentatie. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantische woordembeddings. Word2Vec en GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Taalmodellering. Je eigen embeddings trainen](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrente Neurale Netwerken](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatieve Recurrente Netwerken](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Grote Taalmodellen, Prompt Programming en Few-Shot Taken](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**Natuurlijke Taalverwerking**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Ontdek Natuurlijke Taalverwerking op Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Tekstrepresentatie. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantische woordembeddings. Word2Vec en GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Taalmodellering. Eigen embeddings trainen](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrente Neurale Netwerken](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatieve Recurrente Netwerken](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Grote Taalmodellen, Promptprogrammering en Few-Shot Taken](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Andere AI-technieken** || |
| 21 | [Genetische Algoritmen](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Diepe Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 22 | [Diepe Versterkingsleren](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Multi-Agent Systemen](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI Ethiek** | | |
| 24 | [AI Ethiek en Verantwoordelijke AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Principes van Verantwoordelijke AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| 24 | [AI Ethiek en Verantwoorde AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Principes voor Verantwoorde AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Extra's** | | |
| 25 | [Multi-Modale Netwerken, CLIP en VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Elke les bevat
* Voorbereidend leesmateriaal
* Uitvoerbare Jupyter Notebooks, die vaak specifiek zijn voor het framework (**PyTorch** of **TensorFlow**). Het uitvoerbare notebook bevat ook veel theoretisch materiaal, dus om het onderwerp te begrijpen moet je minstens één versie van het notebook doorlopen (PyTorch of TensorFlow).
* **Labs** beschikbaar voor sommige onderwerpen, waarmee je de kans krijgt om het geleerde materiaal toe te passen op een specifiek probleem.
* Uitvoerbare Jupyter Notebooks, vaak specifiek voor het framework (**PyTorch** of **TensorFlow**). Het uitvoerbare notebook bevat ook veel theoretisch materiaal, dus om het onderwerp te begrijpen moet je minstens één versie van het notebook doornemen (PyTorch of TensorFlow).
* **Labs** beschikbaar voor sommige onderwerpen, waarmee je de kans krijgt om het geleerde toe te passen op een specifiek probleem.
* Sommige secties bevatten links naar [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) modules die gerelateerde onderwerpen behandelen.
## Aan de slag
- We hebben een [setup-les](./lessons/0-course-setup/setup.md) gemaakt om je te helpen bij het instellen van je ontwikkelomgeving. - Voor docenten hebben we ook een [curricula setup-les](./lessons/0-course-setup/for-teachers.md) gemaakt!
- Hoe je [de code uitvoert in VSCode of een Codespace](./lessons/0-course-setup/how-to-run.md)
- We hebben een [setup-les](./lessons/0-course-setup/setup.md) gemaakt om je te helpen met het opzetten van je ontwikkelomgeving. - Voor docenten hebben we ook een [curriculum-setup-les](./lessons/0-course-setup/for-teachers.md) gemaakt!
- Hoe je de [code uitvoert in VSCode of een Codespace](./lessons/0-course-setup/how-to-run.md)
Volg deze stappen:
Fork de Repository: Klik op de "Fork"-knop rechtsboven op deze pagina.
Fork de repository: Klik op de "Fork"-knop rechtsboven op deze pagina.
Clone de Repository: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Clone de repository: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Vergeet niet om deze repo te sterren (🌟) zodat je hem later makkelijker kunt vinden.
Vergeet niet om deze repo te sterren (🌟) zodat je hem later makkelijker kunt terugvinden.
## Ontmoet andere leerlingen
## Ontmoet andere studenten
Word lid van onze [officiële AI Discord-server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) om andere leerlingen te ontmoeten en te netwerken die deze cursus volgen en om ondersteuning te krijgen.
Word lid van onze [officiële AI Discord-server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) om andere studenten te ontmoeten die deze cursus volgen en om ondersteuning te krijgen.
Als je productfeedback of vragen hebt tijdens het bouwen, bezoek dan ons [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Quizzen
> **Een opmerking over quizzen**: Alle quizzen bevinden zich in de Quiz-app map in etc\quiz-app, of [Online Hier](https://ff-quizzes.netlify.app/). Ze zijn gekoppeld vanuit de lessen. De quiz-app kan lokaal worden uitgevoerd of worden gedeployed naar Azure; volg de instructies in de `quiz-app` map. Ze worden geleidelijk vertaald.
> **Een opmerking over quizzen**: Alle quizzen zijn te vinden in de Quiz-app map in etc\quiz-app, of [Online Hier](https://ff-quizzes.netlify.app/). Ze zijn gekoppeld aan de lessen en de quiz-app kan lokaal worden uitgevoerd of worden gedeployed naar Azure; volg de instructies in de `quiz-app` map. Ze worden geleidelijk gelokaliseerd.
## Hulp Gezocht
Heb je suggesties of spelling- of codefouten gevonden? Maak een issue aan of dien een pull request in.
Heb je suggesties of heb je spelfouten of codefouten gevonden? Open een issue of maak een pull request aan.
## Speciale Dank
* **✍️ Hoofdauteur:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Redacteur:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Sketchnote illustrator:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Quizmaker:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Kernbijdragers:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ Hoofdauteur:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Redacteur:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Sketchnote-illustrator:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Quizmaker:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Kernbijdragers:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Andere Leermaterialen
Ons team produceert ook andere leermaterialen! Bekijk:
Ons team maakt ook andere leermaterialen! Bekijk:
- [Generatieve AI voor Beginners](https://aka.ms/genai-beginners)
- [Generatieve AI voor Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generatieve AI met JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generatieve AI met Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI voor Beginners](https://aka.ms/ai-beginners)
- [Data Science voor Beginners](https://aka.ms/datascience-beginners)
- [ML voor Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity voor Beginners](https://github.com/microsoft/Security-101)
- [Webontwikkeling voor Beginners](https://aka.ms/webdev-beginners)
- [IoT voor Beginners](https://aka.ms/iot-beginners)
- [XR Ontwikkeling voor Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [GitHub Copilot Masteren voor Agentisch Gebruik](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [GitHub Copilot Masteren voor C#/.NET Ontwikkelaars](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Kies Je Eigen Copilot Avontuur](https://github.com/microsoft/CopilotAdventures)
- [Generatieve AI voor Beginners](https://aka.ms/genai-beginners)
- [Generatieve AI voor Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generatieve AI met JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generatieve AI met Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI voor Beginners](https://aka.ms/ai-beginners)
- [Datawetenschap voor Beginners](https://aka.ms/datascience-beginners)
- [ML voor Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity voor Beginners](https://github.com/microsoft/Security-101)
- [Webontwikkeling voor Beginners](https://aka.ms/webdev-beginners)
- [IoT voor Beginners](https://aka.ms/iot-beginners)
- [XR-ontwikkeling voor Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot voor Agentisch Gebruik](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot voor C#/.NET Ontwikkelaars](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Kies Je Eigen Copilot Avontuur](https://github.com/microsoft/CopilotAdventures)
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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Kunstig intelligens for nybegynnere - Et læreplan
# Kunstig intelligens for nybegynnere - Et pensum
|![Sketchnote av @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.no.png)|
|:---:|
| AI for nybegynnere - _Sketchnote av [@girlie_mac](https://twitter.com/girlie_mac)_ |
|![Sketchnote av @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.no.png)|
|:---:|
| AI For Beginners - _Sketchnote av [@girlie_mac](https://twitter.com/girlie_mac)_ |
Utforsk verden av **kunstig intelligens** (AI) med vår 12-ukers, 24-leksjons læreplan! Den inkluderer praktiske leksjoner, quizer og laboratorier. Læreplanen er nybegynnervennlig og dekker verktøy som TensorFlow og PyTorch, samt etikk i AI.
Utforsk verden av **Kunstig Intelligens** (AI) med vårt 12-ukers, 24-leksjons pensum! Det inkluderer praktiske leksjoner, quizzer og laboratorier. Pensumet er nybegynnervennlig og dekker verktøy som TensorFlow og PyTorch, samt etikk innen AI.
### 🌐 Støtte for flere språk
### 🌐 Støtte for flere språk
#### Støttet via GitHub Action (Automatisk og alltid oppdatert)
#### Støttet via GitHub Action (Automatisk og alltid oppdatert)
[Fransk](../fr/README.md) | [Spansk](../es/README.md) | [Tysk](../de/README.md) | [Russisk](../ru/README.md) | [Arabisk](../ar/README.md) | [Persisk (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Kinesisk (forenklet)](../zh/README.md) | [Kinesisk (tradisjonell, Macau)](../mo/README.md) | [Kinesisk (tradisjonell, Hong Kong)](../hk/README.md) | [Kinesisk (tradisjonell, Taiwan)](../tw/README.md) | [Japansk](../ja/README.md) | [Koreansk](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portugisisk (Portugal)](../pt/README.md) | [Portugisisk (Brasil)](../br/README.md) | [Italiensk](../it/README.md) | [Polsk](../pl/README.md) | [Tyrkisk](../tr/README.md) | [Gresk](../el/README.md) | [Thai](../th/README.md) | [Svensk](../sv/README.md) | [Dansk](../da/README.md) | [Norsk](./README.md) | [Finsk](../fi/README.md) | [Nederlandsk](../nl/README.md) | [Hebraisk](../he/README.md) | [Vietnamesisk](../vi/README.md) | [Indonesisk](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filippinsk)](../tl/README.md) | [Swahili](../sw/README.md) | [Ungarsk](../hu/README.md) | [Tsjekkisk](../cs/README.md) | [Slovakisk](../sk/README.md) | [Rumensk](../ro/README.md) | [Bulgarsk](../bg/README.md) | [Serbisk (kyrillisk)](../sr/README.md) | [Kroatisk](../hr/README.md) | [Slovensk](../sl/README.md) | [Ukrainsk](../uk/README.md) | [Burmesisk (Myanmar)](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](./README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Hvis du ønsker flere oversettelser, finner du støttede språk [her](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Hvis du ønsker å få støtte for flere oversettelser, er språkene som støttes listet opp [her](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Bli med i fellesskapet
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Bli med i fellesskapet
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Hva du vil lære
## Hva du vil lære
**[Tankekart for kurset](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[Tankekart for kurset](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
I denne læreplanen vil du lære:
I dette pensumet vil du lære:
* Ulike tilnærminger til kunstig intelligens, inkludert den "gode gamle" symbolske tilnærmingen med **kunnskapsrepresentasjon** og resonnering ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Nevrale nettverk** og **dyp læring**, som er kjernen i moderne AI. Vi vil illustrere konseptene bak disse viktige temaene ved hjelp av kode i to av de mest populære rammeverkene - [TensorFlow](http://Tensorflow.org) og [PyTorch](http://pytorch.org).
* **Nevrale arkitekturer** for arbeid med bilder og tekst. Vi vil dekke nyere modeller, men kan mangle noe på det aller nyeste.
* Mindre populære AI-tilnærminger, som **genetiske algoritmer** og **multi-agent-systemer**.
* Ulike tilnærminger til Kunstig Intelligens, inkludert den "gode gamle" symbolske tilnærmingen med **Kunnskapsrepresentasjon** og resonnering ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Nevrale nettverk** og **Dyp læring**, som er kjernen i moderne AI. Vi vil illustrere konseptene bak disse viktige temaene med kode i to av de mest populære rammeverkene - [TensorFlow](http://Tensorflow.org) og [PyTorch](http://pytorch.org).
* **Nevrale arkitekturer** for arbeid med bilder og tekst. Vi vil dekke nyere modeller, men kan være litt mangelfulle når det gjelder det nyeste innen forskning.
* Mindre populære AI-tilnærminger, som **Genetiske algoritmer** og **Multi-Agent Systems**.
Hva vi ikke vil dekke i denne læreplanen:
Hva vi ikke vil dekke i dette pensumet:
> [Finn alle tilleggsmaterialer for dette kurset i vår Microsoft Learn-samling](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Finn alle tilleggsmaterialer for dette kurset i vår Microsoft Learn-samling](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Forretningsbruk av **AI i næringslivet**. Vurder å ta [Introduksjon til AI for forretningsbrukere](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) læringssti på Microsoft Learn, eller [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), utviklet i samarbeid med [INSEAD](https://www.insead.edu/).
* **Klassisk maskinlæring**, som er godt beskrevet i vår [Maskinlæring for nybegynnere-læreplan](http://github.com/Microsoft/ML-for-Beginners).
* Praktiske AI-applikasjoner bygget ved hjelp av **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. For dette anbefaler vi at du starter med moduler på Microsoft Learn for [visjon](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [naturlig språkbehandling](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generativ AI med Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** og andre.
* Spesifikke ML **skyrammeverk**, som [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), eller [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Vurder å bruke [Bygg og drift maskinlæringsløsninger med Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) og [Bygg og drift maskinlæringsløsninger med Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) læringsstier.
* **Samtale-AI** og **chatboter**. Det finnes en egen [Lag samtale-AI-løsninger](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) læringssti, og du kan også referere til [denne bloggposten](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) for mer detalj.
* **Dyp matematikk** bak dyp læring. For dette anbefaler vi [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) av Ian Goodfellow, Yoshua Bengio og Aaron Courville, som også er tilgjengelig online på [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Forretningscaser for bruk av **AI i næringslivet**. Vurder å ta [Introduksjon til AI for forretningsbrukere](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) læringssti på Microsoft Learn, eller [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), utviklet i samarbeid med [INSEAD](https://www.insead.edu/).
* **Klassisk maskinlæring**, som er godt beskrevet i vårt [Maskinlæring for nybegynnere pensum](http://github.com/Microsoft/ML-for-Beginners).
* Praktiske AI-applikasjoner bygget med **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. For dette anbefaler vi at du starter med moduler på Microsoft Learn for [visjon](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [naturlig språkbehandling](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generativ AI med Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** og andre.
* Spesifikke ML **Cloud Frameworks**, som [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), eller [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Vurder å bruke [Bygg og drift maskinlæringsløsninger med Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) og [Bygg og drift maskinlæringsløsninger med Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) læringsstier.
* **Samtale-AI** og **Chat Bots**. Det finnes en egen [Lag samtale-AI-løsninger](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) læringssti, og du kan også referere til [denne bloggposten](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) for mer detaljer.
* **Dyp matematikk** bak dyp læring. For dette anbefaler vi [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) av Ian Goodfellow, Yoshua Bengio og Aaron Courville, som også er tilgjengelig online på [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
For en myk introduksjon til _AI i skyen_-temaer kan du vurdere å ta [Kom i gang med kunstig intelligens på Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) læringssti.
For en enkel introduksjon til _AI i skyen_-temaer kan du vurdere å ta [Kom i gang med kunstig intelligens på Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) læringssti.
# Innhold
# Innhold
| | Leksjonslenke | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Kursoppsett](./lessons/0-course-setup/setup.md) | [Sett opp ditt utviklingsmiljø](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Introduksjon til AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Introduksjon og historien til AI](./lessons/1-Intro/README.md) | - | - |
| II | **Symbolsk AI** |
| 02 | [Kunnskapsrepresentasjon og ekspertsystemer](./lessons/2-Symbolic/README.md) | [Ekspertsystemer](./lessons/2-Symbolic/Animals.ipynb) / [Ontologi](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Konseptgraf](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Introduksjon til nevrale nettverk**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Flerlags perceptron og lage vårt eget rammeverk](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Intro til rammeverk (PyTorch/TensorFlow) og overtilpasning](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| | Leksjonslenke | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Kursoppsett](./lessons/0-course-setup/setup.md) | [Sett opp ditt utviklingsmiljø](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Introduksjon til AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Introduksjon og historie om AI](./lessons/1-Intro/README.md) | - | - |
| II | **Symbolsk AI** |
| 02 | [Kunnskapsrepresentasjon og ekspertsystemer](./lessons/2-Symbolic/README.md) | [Ekspertsystemer](./lessons/2-Symbolic/Animals.ipynb) / [Ontologi](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Konseptgraf](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Introduksjon til nevrale nettverk**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Multi-lags perceptron og lage vårt eget rammeverk](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Introduksjon til rammeverk (PyTorch/TensorFlow) og overtilpasning](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Datamaskinsyn**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Utforsk datamaskinsyn på Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Intro til datamaskinsyn. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 06 | [Introduksjon til datamaskinsyn. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvolusjonelle nevrale nettverk](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN-arkitekturer](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Forhåndstrente nettverk og overføringslæring](./lessons/4-ComputerVision/08-TransferLearning/README.md) og [Treningsmetoder](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoenkodere og VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
@ -86,20 +86,20 @@ For en myk introduksjon til _AI i skyen_-temaer kan du vurdere å ta [Kom i gang
| 11 | [Objektdeteksjon](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantisk segmentering. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Naturlig språkbehandling**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Utforsk naturlig språkbehandling på Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Tekstrepresentasjon. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantiske ordinnbeddinger. Word2Vec og GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Språkmodellering. Tren dine egne innbeddinger](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurrente nevrale nettverk](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative rekurrente nettverk](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Navngitt enhetsgjenkjenning](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Store språkmodeller, prompt-programmering og få-skudd oppgaver](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Tekstrepresentasjon. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantiske ord-embeddings. Word2Vec og GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Språkmodellering. Tren dine egne embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurrente nevrale nettverk](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative rekurrente nettverk](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Navngitt enhetsgjenkjenning](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Store språkmodeller, prompt-programmering og få-skudd oppgaver](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Andre AI-teknikker** || |
| 21 | [Genetiske algoritmer](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Dyp forsterkningslæring](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Multi-agent systemer](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI-etikk** | | |
| 24 | [AI-etikk og ansvarlig AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Prinsipper for ansvarlig AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| VII | **AI Etikk** | | |
| 24 | [AI Etikk og ansvarlig AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Prinsipper for ansvarlig AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Ekstra** | | |
| 25 | [Multi-modale nettverk, CLIP og VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
@ -107,7 +107,7 @@ For en myk introduksjon til _AI i skyen_-temaer kan du vurdere å ta [Kom i gang
* Forhåndslesingsmateriale
* Kjørbare Jupyter Notebooks, som ofte er spesifikke for rammeverket (**PyTorch** eller **TensorFlow**). Den kjørbare notebooken inneholder også mye teoretisk materiale, så for å forstå emnet må du gå gjennom minst én versjon av notebooken (enten PyTorch eller TensorFlow).
* **Labs** tilgjengelig for noen emner, som gir deg mulighet til å prøve å anvende materialet du har lært på et spesifikt problem.
* **Labs** tilgjengelig for noen emner, som gir deg muligheten til å prøve å anvende materialet du har lært på et spesifikt problem.
* Noen seksjoner inneholder lenker til [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) moduler som dekker relaterte emner.
## Kom i gang
@ -117,11 +117,11 @@ For en myk introduksjon til _AI i skyen_-temaer kan du vurdere å ta [Kom i gang
Følg disse stegene:
Fork repoen: Klikk på "Fork"-knappen øverst til høyre på denne siden.
Fork repository: Klikk på "Fork"-knappen øverst til høyre på denne siden.
Klon repoen: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Clone repository: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Ikke glem å stjerne (🌟) denne repoen for å finne den enklere senere.
Ikke glem å stjerne (🌟) dette repoet for å finne det enklere senere.
## Møt andre lærende
@ -130,7 +130,7 @@ Bli med på vår [offisielle AI Discord-server](https://aka.ms/genai-discord?WT.
Hvis du har produktfeedback eller spørsmål mens du bygger, besøk vårt [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Quizer
> **En merknad om quizene**: Alle quizene finnes i Quiz-app-mappen i etc\quiz-app, eller [Online her](https://ff-quizzes.netlify.app/). De er lenket fra leksjonene, og quiz-appen kan kjøres lokalt eller distribueres til Azure; følg instruksjonene i `quiz-app`-mappen. De blir gradvis lokalisert.
> **En merknad om quizer**: Alle quizer finnes i Quiz-app-mappen i etc\quiz-app, eller [Online Her](https://ff-quizzes.netlify.app/). De er lenket fra leksjonene, og quiz-appen kan kjøres lokalt eller distribueres til Azure; følg instruksjonene i `quiz-app`-mappen. De blir gradvis lokalisert.
## Hjelp ønskes
Har du forslag eller funnet skrivefeil eller kodefeil? Opprett en issue eller lag en pull request.
@ -165,4 +165,4 @@ Teamet vårt lager andre læreplaner! Sjekk ut:
---
**Ansvarsfraskrivelse**:
Dette dokumentet er oversatt ved hjelp av AI-oversettelsestjenesten [Co-op Translator](https://github.com/Azure/co-op-translator). Selv om vi tilstreber nøyaktighet, vær oppmerksom på at automatiske oversettelser kan inneholde feil eller unøyaktigheter. Det originale dokumentet på sitt opprinnelige språk bør anses som den autoritative kilden. For kritisk informasjon anbefales profesjonell menneskelig oversettelse. Vi er ikke ansvarlige for eventuelle misforståelser eller feiltolkninger som oppstår ved bruk av denne oversettelsen.
Dette dokumentet er oversatt ved hjelp av AI-oversettelsestjenesten [Co-op Translator](https://github.com/Azure/co-op-translator). Selv om vi streber etter nøyaktighet, vær oppmerksom på at automatiserte oversettelser kan inneholde feil eller unøyaktigheter. Det originale dokumentet på sitt opprinnelige språk bør anses som den autoritative kilden. For kritisk informasjon anbefales profesjonell menneskelig oversettelse. Vi er ikke ansvarlige for eventuelle misforståelser eller feiltolkninger som oppstår ved bruk av denne oversettelsen.

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@ -1,8 +1,8 @@
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@ -21,21 +21,21 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# ਸ਼ੁਰੂਆਤੀ ਲਈ ਕ੍ਰਿਤ੍ਰਿਮ ਬੁੱਧੀ - ਇੱਕ ਪਾਠਕ੍ਰਮ
# ਸ਼ੁਰੂਆਤੀ ਲਈ ਕ੍ਰਿਤਮ ਬੁੱਧੀ - ਇੱਕ ਪਾਠਕ੍ਰਮ
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.pa.png)|
|:---:|
| ਸ਼ੁਰੂਆਤੀ ਲਈ AI - _[@girlie_mac](https://twitter.com/girlie_mac) ਦੁਆਰਾ ਬਣਾਇਆ ਗਿਆ ਸਕੈਚਨੋਟ_ |
| ਸ਼ੁਰੂਆਤੀ ਲਈ AI - _[@girlie_mac](https://twitter.com/girlie_mac) ਦੁਆਰਾ ਬਣਾਈ ਗਈ ਸਕੈਚਨੋਟ_ |
**ਕ੍ਰਿਤ੍ਰਿਮ ਬੁੱਧੀ** (AI) ਦੀ ਦੁਨੀਆ ਨੂੰ ਖੋਜੋ ਸਾਡੇ 12 ਹਫ਼ਤਿਆਂ ਦੇ, 24 ਪਾਠਾਂ ਵਾਲੇ ਪਾਠਕ੍ਰਮ ਨਾਲ! ਇਸ ਵਿੱਚ ਵਿਹਾਰਕ ਪਾਠ, ਪ੍ਰਸ਼ਨੋਤਰੀ ਅਤੇ ਪ੍ਰਯੋਗਸ਼ਾਲਾਵਾਂ ਸ਼ਾਮਲ ਹਨ। ਇਹ ਪਾਠਕ੍ਰਮ ਸ਼ੁਰੂਆਤੀ ਲਈ ਅਨੁਕੂਲ ਹੈ ਅਤੇ ਇਸ ਵਿੱਚ TensorFlow ਅਤੇ PyTorch ਵਰਗੇ ਟੂਲਾਂ ਦੇ ਨਾਲ ਨਾਲ AI ਵਿੱਚ ਨੈਤਿਕਤਾ ਵੀ ਸ਼ਾਮਲ ਹੈ।
**ਕ੍ਰਿਤਮ ਬੁੱਧੀ** (AI) ਦੀ ਦੁਨੀਆ ਦੀ ਖੋਜ ਕਰੋ ਸਾਡੇ 12 ਹਫ਼ਤਿਆਂ ਦੇ, 24 ਪਾਠਾਂ ਦੇ ਪਾਠਕ੍ਰਮ ਨਾਲ! ਇਸ ਵਿੱਚ ਵਿਹੰਗੀ ਪਾਠ, ਪ੍ਰਸ਼ਨੋਤਰੀ ਅਤੇ ਪ੍ਰਯੋਗਸ਼ਾਲਾਵਾਂ ਸ਼ਾਮਲ ਹਨ। ਪਾਠਕ੍ਰਮ ਸ਼ੁਰੂਆਤੀ ਲਈ ਅਨੁਕੂਲ ਹੈ ਅਤੇ TensorFlow ਅਤੇ PyTorch ਵਰਗੇ ਸੰਦਾਂ ਨਾਲ ਨਾਲ AI ਵਿੱਚ ਨੈਤਿਕਤਾ ਨੂੰ ਵੀ ਕਵਰ ਕਰਦਾ ਹੈ।
### 🌐 ਬਹੁ-ਭਾਸ਼ਾਈ ਸਹਾਇਤਾ
### 🌐 ਬਹੁ-ਭਾਸ਼ਾ ਸਹਾਇਤਾ
#### GitHub Action ਰਾਹੀਂ ਸਹਾਇਕ (ਆਟੋਮੈਟਿਕ ਅਤੇ ਹਮੇਸ਼ਾ ਅਪ-ਟੂ-ਡੇਟ)
#### GitHub Action ਰਾਹੀਂ ਸਹਾਇਤਾਪ੍ਰਾਪਤ (ਸਵੈਚਾਲਿਤ ਅਤੇ ਹਮੇਸ਼ਾ ਅਪ-ਟੂ-ਡੇਟ)
[ਫਰਾਂਸੀਸੀ](../fr/README.md) | [ਸਪੇਨੀ](../es/README.md) | [ਜਰਮਨ](../de/README.md) | [ਰੂਸੀ](../ru/README.md) | [ਅਰਬੀ](../ar/README.md) | [ਫ਼ਾਰਸੀ](../fa/README.md) | [ਉਰਦੂ](../ur/README.md) | [ਚੀਨੀ (ਸਰਲ)](../zh/README.md) | [ਚੀਨੀ (ਪਾਰੰਪਰਿਕ, ਮਕਾਉ)](../mo/README.md) | [ਚੀਨੀ (ਪਾਰੰਪਰਿਕ, ਹਾਂਗਕਾਂਗ)](../hk/README.md) | [ਚੀਨੀ (ਪਾਰੰਪਰਿਕ, ਤਾਈਵਾਨ)](../tw/README.md) | [ਜਾਪਾਨੀ](../ja/README.md) | [ਕੋਰੀਆਈ](../ko/README.md) | [ਹਿੰਦੀ](../hi/README.md) | [ਬੰਗਾਲੀ](../bn/README.md) | [ਮਰਾਠੀ](../mr/README.md) | [ਨੇਪਾਲੀ](../ne/README.md) | [ਪੰਜਾਬੀ (ਗੁਰਮੁਖੀ)](./README.md) | [ਪੁਰਤਗਾਲੀ (ਪੁਰਤਗਾਲ)](../pt/README.md) | [ਪੁਰਤਗਾਲੀ (ਬ੍ਰਾਜ਼ੀਲ)](../br/README.md) | [ਇਟਾਲਵੀ](../it/README.md) | [ਪੋਲਿਸ਼](../pl/README.md) | [ਤੁਰਕੀ](../tr/README.md) | [ਯੂਨਾਨੀ](../el/README.md) | [ਥਾਈ](../th/README.md) | [ਸਵੀਡਿਸ਼](../sv/README.md) | [ਡੈਨਿਸ਼](../da/README.md) | [ਨਾਰਵੇਜੀਅਨ](../no/README.md) | [ਫਿਨਿਸ਼](../fi/README.md) | [ਡੱਚ](../nl/README.md) | [ਹਿਬਰੂ](../he/README.md) | [ਵਿਯਤਨਾਮੀ](../vi/README.md) | [ਇੰਡੋਨੇਸ਼ੀਆਈ](../id/README.md) | [ਮਲੇ](../ms/README.md) | [ਟੈਗਾਲੋਗ (ਫਿਲੀਪੀਨੋ)](../tl/README.md) | [ਸਵਾਹਿਲੀ](../sw/README.md) | [ਹੰਗਰੀਅਨ](../hu/README.md) | [ਚੈਕ](../cs/README.md) | [ਸਲੋਵਾਕ](../sk/README.md) | [ਰੋਮਾਨੀਅਨ](../ro/README.md) | [ਬੁਲਗਾਰੀਆਈ](../bg/README.md) | [ਸਰਬੀਅਨ (ਸਿਰਿਲਿਕ)](../sr/README.md) | [ਕਰੋਏਸ਼ੀਆਈ](../hr/README.md) | [ਸਲੋਵੇਨੀਆਈ](../sl/README.md) | [ਯੂਕਰੇਨੀ](../uk/README.md) | [ਬਰਮੀ (ਮਿਆਂਮਾਰ)](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](./README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**ਜੇ ਤੁਸੀਂ ਹੋਰ ਭਾਸ਼ਾਵਾਂ ਵਿੱਚ ਅਨੁਵਾਦ ਕਰਵਾਉਣਾ ਚਾਹੁੰਦੇ ਹੋ, ਤਾਂ ਸਹਾਇਕ ਭਾਸ਼ਾਵਾਂ ਦੀ ਸੂਚੀ [ਇੱਥੇ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) ਮਿਲੇਗੀ।**
**ਜੇ ਤੁਸੀਂ ਹੋਰ ਭਾਸ਼ਾਵਾਂ ਵਿੱਚ ਅਨੁਵਾਦ ਕਰਵਾਉਣਾ ਚਾਹੁੰਦੇ ਹੋ ਤਾਂ ਸਹਾਇਤਾਪ੍ਰਾਪਤ ਭਾਸ਼ਾਵਾਂ ਦੀ ਸੂਚੀ [ਇੱਥੇ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) ਦਿੱਤੀ ਗਈ ਹੈ।**
## ਕਮਿਊਨਿਟੀ ਵਿੱਚ ਸ਼ਾਮਲ ਹੋਵੋ
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -46,123 +46,124 @@ CO_OP_TRANSLATOR_METADATA:
ਇਸ ਪਾਠਕ੍ਰਮ ਵਿੱਚ, ਤੁਸੀਂ ਸਿੱਖੋਗੇ:
* ਕ੍ਰਿਤ੍ਰਿਮ ਬੁੱਧੀ ਦੇ ਵੱਖ-ਵੱਖ ਪਹੁੰਚਾਂ, ਜਿਵੇਂ ਕਿ "ਪੁਰਾਣਾ" ਪ੍ਰਤੀਕਾਤਮਕ ਪਹੁੰਚ ਜਿਸ ਵਿੱਚ **ਗਿਆਨ ਪ੍ਰਸਤੁਤੀ** ਅਤੇ ਤਰਕ ਸ਼ਾਮਲ ਹਨ ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))।
* **ਨਿਊਰਲ ਨੈੱਟਵਰਕਸ** ਅਤੇ **ਡੀਪ ਲਰਨਿੰਗ**, ਜੋ ਆਧੁਨਿਕ AI ਦਾ ਕੇਂਦਰ ਹਨ। ਅਸੀਂ ਇਨ੍ਹਾਂ ਮਹੱਤਵਪੂਰਨ ਵਿਸ਼ਿਆਂ ਦੇ ਪਿੱਛੇ ਦੇ ਸੰਕਲਪਾਂ ਨੂੰ ਦੋ ਸਭ ਤੋਂ ਪ੍ਰਸਿੱਧ ਫਰੇਮਵਰਕਸ - [TensorFlow](http://Tensorflow.org) ਅਤੇ [PyTorch](http://pytorch.org) ਵਿੱਚ ਕੋਡ ਦੀ ਵਰਤੋਂ ਕਰਕੇ ਦਰਸਾਵਾਂਗੇ।
* ਚਿੱਤਰਾਂ ਅਤੇ ਪਾਠਾਂ ਨਾਲ ਕੰਮ ਕਰਨ ਲਈ **ਨਿਊਰਲ ਆਰਕੀਟੈਕਚਰਸ**। ਅਸੀਂ ਹਾਲੀਆ ਮਾਡਲਾਂ ਨੂੰ ਕਵਰ ਕਰਾਂਗੇ ਪਰ ਸ਼ਾਇਦ ਸਟੇਟ-ਆਫ-ਦ-ਆਰਟ ਵਿੱਚ ਥੋੜੇ ਘਾਟੇ ਹੋ ਸਕਦੇ ਹਨ।
* ਕ੍ਰਿਤਮ ਬੁੱਧੀ ਦੇ ਵੱਖ-ਵੱਖ ਪਹੁੰਚਾਂ, ਜਿਵੇਂ ਕਿ "ਪੁਰਾਣਾ ਚੰਗਾ" ਪ੍ਰਤੀਕਾਤਮਕ ਪਹੁੰਚ **ਗਿਆਨ ਪ੍ਰਤੀਨਿਧੀ** ਅਤੇ ਤਰਕ ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))।
* **ਨਿਊਰਲ ਨੈਟਵਰਕਸ** ਅਤੇ **ਡੀਪ ਲਰਨਿੰਗ**, ਜੋ ਆਧੁਨਿਕ AI ਦੇ ਕੇਂਦਰ ਵਿੱਚ ਹਨ। ਅਸੀਂ ਇਨ੍ਹਾਂ ਮਹੱਤਵਪੂਰਨ ਵਿਸ਼ਿਆਂ ਦੇ ਪਿਛਲੇ ਸਿਧਾਂਤਾਂ ਨੂੰ ਦੋ ਸਭ ਤੋਂ ਪ੍ਰਸਿੱਧ ਫਰੇਮਵਰਕਸ - [TensorFlow](http://Tensorflow.org) ਅਤੇ [PyTorch](http://pytorch.org) ਵਿੱਚ ਕੋਡ ਦੀ ਵਰਤੋਂ ਕਰਕੇ ਦਰਸਾਵਾਂਗੇ।
* ਚਿੱਤਰਾਂ ਅਤੇ ਪਾਠਾਂ ਨਾਲ ਕੰਮ ਕਰਨ ਲਈ **ਨਿਊਰਲ ਆਰਕੀਟੈਕਚਰਸ**। ਅਸੀਂ ਹਾਲੀਆ ਮਾਡਲਾਂ ਨੂੰ ਕਵਰ ਕਰਾਂਗੇ ਪਰ ਸਟੇਟ-ਆਫ-ਦ-ਆਰਟ ਵਿੱਚ ਕੁਝ ਘਾਟ ਹੋ ਸਕਦੀ ਹੈ।
* ਘੱਟ ਪ੍ਰਸਿੱਧ AI ਪਹੁੰਚਾਂ, ਜਿਵੇਂ ਕਿ **ਜੈਨੇਟਿਕ ਐਲਗੋਰਿਥਮਸ** ਅਤੇ **ਮਲਟੀ-ਏਜੰਟ ਸਿਸਟਮਸ**।
ਜੋ ਅਸੀਂ ਇਸ ਪਾਠਕ੍ਰਮ ਵਿੱਚ ਕਵਰ ਨਹੀਂ ਕਰਾਂਗੇ:
> [ਇਸ ਕੋਰਸ ਲਈ ਸਾਰੇ ਵਾਧੂ ਸਰੋਤ ਸਾਡੇ Microsoft Learn ਕਲੈਕਸ਼ਨ ਵਿੱਚ ਲੱਭੋ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [ਇਸ ਕੋਰਸ ਲਈ ਸਾਰੇ ਵਾਧੂ ਸਰੋਤ Microsoft Learn ਕਲੈਕਸ਼ਨ ਵਿੱਚ ਲੱਭੋ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **ਵਪਾਰ ਵਿੱਚ AI ਦੀ ਵਰਤੋਂ ਦੇ ਕਾਰੋਬਾਰੀ ਕੇਸ**। Microsoft Learn 'ਤੇ [ਵਪਾਰਕ ਉਪਭੋਗਤਾਵਾਂ ਲਈ AI ਦਾ ਪਰਿਚਯ](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) ਲਰਨਿੰਗ ਪਾਠ ਜਾਂ [AI ਬਿਜ਼ਨਸ ਸਕੂਲ](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), ਜੋ [INSEAD](https://www.insead.edu/) ਦੇ ਸਹਿਯੋਗ ਨਾਲ ਵਿਕਸਿਤ ਕੀਤਾ ਗਿਆ ਹੈ, ਲੈਣ ਦੀ ਸਿਫਾਰਸ਼ ਕੀਤੀ ਜਾਂਦੀ ਹੈ।
* **ਵਪਾਰ ਵਿੱਚ AI ਦੀ ਵਰਤੋਂ** ਦੇ ਕਾਰੋਬਾਰੀ ਕੇਸ। [ਵਪਾਰਕ ਉਪਭੋਗਤਾਵਾਂ ਲਈ AI ਦਾ ਪਰਿਚਯ](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) ਲਰਨਿੰਗ ਪਾਠਕ੍ਰਮ ਜਾਂ [AI ਬਿਜ਼ਨਸ ਸਕੂਲ](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), ਜੋ [INSEAD](https://www.insead.edu/) ਦੇ ਸਹਿਯੋਗ ਨਾਲ ਵਿਕਸਿਤ ਕੀਤਾ ਗਿਆ ਹੈ।
* **ਕਲਾਸਿਕ ਮਸ਼ੀਨ ਲਰਨਿੰਗ**, ਜੋ ਸਾਡੇ [ਸ਼ੁਰੂਆਤੀ ਲਈ ਮਸ਼ੀਨ ਲਰਨਿੰਗ ਪਾਠਕ੍ਰਮ](http://github.com/Microsoft/ML-for-Beginners) ਵਿੱਚ ਚੰਗੀ ਤਰ੍ਹਾਂ ਵਰਣਨ ਕੀਤਾ ਗਿਆ ਹੈ।
* **[ਕਾਗਨੀਟਿਵ ਸਰਵਿਸਿਜ਼](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** ਦੀ ਵਰਤੋਂ ਕਰਕੇ ਬਣਾਏ ਗਏ ਵਿਹਾਰਕ AI ਐਪਲੀਕੇਸ਼ਨ। ਇਸ ਲਈ, ਅਸੀਂ ਸਿਫਾਰਸ਼ ਕਰਦੇ ਹਾਂ ਕਿ ਤੁਸੀਂ Microsoft Learn ਦੇ ਮਾਡਿਊਲਾਂ ਨਾਲ ਸ਼ੁਰੂ ਕਰੋ ਜਿਵੇਂ ਕਿ [ਦ੍ਰਿਸ਼ਟੀ](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [ਕੁਦਰਤੀ ਭਾਸ਼ਾ ਪ੍ਰਕਿਰਿਆ](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI Service ਨਾਲ ਜੈਨਰੇਟਿਵ AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** ਅਤੇ ਹੋਰ।
* ਖਾਸ ML **ਕਲਾਉਡ ਫਰੇਮਵਰਕਸ**, ਜਿਵੇਂ ਕਿ [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), ਜਾਂ [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)। [Azure Machine Learning ਨਾਲ ਮਸ਼ੀਨ ਲਰਨਿੰਗ ਹੱਲ ਬਣਾਓ ਅਤੇ ਚਲਾਓ](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) ਅਤੇ [Azure Databricks ਨਾਲ ਮਸ਼ੀਨ ਲਰਨਿੰਗ ਹੱਲ ਬਣਾਓ ਅਤੇ ਚਲਾਓ](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) ਲਰਨਿੰਗ ਪਾਠਾਂ ਦੀ ਵਰਤੋਂ ਕਰਨ ਦੀ ਸਿਫਾਰਸ਼ ਕੀਤੀ ਜਾਂਦੀ ਹੈ।
* **ਕੰਵਰਸੇਸ਼ਨਲ AI** ਅਤੇ **ਚੈਟ ਬੌਟਸ**। ਇਸ ਲਈ ਇੱਕ ਵੱਖਰਾ [ਕੰਵਰਸੇਸ਼ਨਲ AI ਹੱਲ ਬਣਾਓ](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) ਲਰਨਿੰਗ ਪਾਠ ਹੈ, ਅਤੇ ਤੁਸੀਂ ਹੋਰ ਵੇਰਵੇ ਲਈ [ਇਸ ਬਲੌਗ ਪੋਸਟ](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) ਨੂੰ ਵੀ ਵੇਖ ਸਕਦੇ ਹੋ।
* **ਡੀਪ ਲਰਨਿੰਗ ਦੇ ਪਿੱਛੇ ਦੀ ਗਹਿਰਾਈ ਵਾਲੀ ਗਣਿਤ**। ਇਸ ਲਈ, ਅਸੀਂ ਸਿਫਾਰਸ਼ ਕਰਦੇ ਹਾਂ [ਡੀਪ ਲਰਨਿੰਗ](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) ਇਆਨ ਗੁਡਫੈਲੋ, ਯੋਸ਼ੂਆ ਬੈਂਜਿਓ ਅਤੇ ਐਰਨ ਕੌਰਵਿਲ ਦੁਆਰਾ, ਜੋ [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) 'ਤੇ ਵੀ ਉਪਲਬਧ ਹੈ।
* **[ਕਾਗਨੀਟਿਵ ਸਰਵਿਸਿਜ਼](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** ਦੀ ਵਰਤੋਂ ਕਰਕੇ ਬਣਾਈਆਂ ਗਈਆਂ ਪ੍ਰਯੋਗਸ਼ੀਲ AI ਐਪਲੀਕੇਸ਼ਨ। ਇਸ ਲਈ, ਅਸੀਂ Microsoft Learn ਦੇ ਮਾਡਿਊਲਾਂ ਨਾਲ ਸ਼ੁਰੂ ਕਰਨ ਦੀ ਸਿਫਾਰਸ਼ ਕਰਦੇ ਹਾਂ [ਦ੍ਰਿਸ਼](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [ਕੁਦਰਤੀ ਭਾਸ਼ਾ ਪ੍ਰੋਸੈਸਿੰਗ](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI Service ਨਾਲ ਜਨਰੇਟਿਵ AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** ਅਤੇ ਹੋਰ।
* **ਮਸ਼ੀਨ ਲਰਨਿੰਗ ਕਲਾਉਡ ਫਰੇਮਵਰਕਸ**, ਜਿਵੇਂ ਕਿ [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), ਜਾਂ [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)। [Azure Machine Learning ਨਾਲ ਮਸ਼ੀਨ ਲਰਨਿੰਗ ਹੱਲ ਬਣਾਓ ਅਤੇ ਚਲਾਓ](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) ਅਤੇ [Azure Databricks ਨਾਲ ਮਸ਼ੀਨ ਲਰਨਿੰਗ ਹੱਲ ਬਣਾਓ ਅਤੇ ਚਲਾਓ](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) ਲਰਨਿੰਗ ਪਾਠਕ੍ਰਮਾਂ ਦੀ ਸਿਫਾਰਸ਼ ਕੀਤੀ ਜਾਂਦੀ ਹੈ।
* **ਵਾਤਾਂਸ਼ੀ AI** ਅਤੇ **ਚੈਟ ਬੋਟਸ**। [ਵਾਤਾਂਸ਼ੀ AI ਹੱਲ ਬਣਾਓ](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) ਲਰਨਿੰਗ ਪਾਠਕ੍ਰਮ ਹੈ, ਅਤੇ ਤੁਸੀਂ ਹੋਰ ਵੇਰਵੇ ਲਈ [ਇਹ ਬਲੌਗ ਪੋਸਟ](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) ਨੂੰ ਵੀ ਦੇਖ ਸਕਦੇ ਹੋ।
* **ਡੀਪ ਲਰਨਿੰਗ ਦੇ ਡੀਪ ਗਣਿਤ**। ਇਸ ਲਈ, ਅਸੀਂ Ian Goodfellow, Yoshua Bengio ਅਤੇ Aaron Courville ਦੁਆਰਾ [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) ਦੀ ਸਿਫਾਰਸ਼ ਕਰਦੇ ਹਾਂ, ਜੋ [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) 'ਤੇ ਆਨਲਾਈਨ ਉਪਲਬਧ ਹੈ।
ਕਲਾਉਡ ਵਿੱਚ _AI_ ਦੇ ਵਿਸ਼ਿਆਂ ਲਈ ਹੌਲੀ ਸ਼ੁਰੂਆਤ ਕਰਨ ਲਈ ਤੁਸੀਂ [Azure 'ਤੇ ਕ੍ਰਿਤ੍ਰਿਮ ਬੁੱਧੀ ਨਾਲ ਸ਼ੁਰੂ ਕਰੋ](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) ਲਰਨਿੰਗ ਪਾਠ ਲੈ ਸਕਦੇ ਹੋ।
ਕਲਾਉਡ ਵਿੱਚ _AI_ ਦੇ ਵਿਸ਼ਿਆਂ ਲਈ ਹੌਲੀ ਸ਼ੁਰੂਆਤ ਕਰਨ ਲਈ ਤੁਸੀਂ [Azure 'ਤੇ ਕ੍ਰਿਤਮ ਬੁੱਧੀ ਨਾਲ ਸ਼ੁਰੂ ਕਰੋ](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) ਲਰਨਿੰਗ ਪਾਠਕ੍ਰਮ ਲੈ ਸਕਦੇ ਹੋ।
# ਸਮੱਗਰੀ
| | ਪਾਠ ਲਿੰਕ | PyTorch/Keras/TensorFlow | ਪ੍ਰਯੋਗਸ਼ਾਲਾ |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [ਕੋਰਸ ਸੈਟਅੱਪ](./lessons/0-course-setup/setup.md) | [ਆਪਣੇ ਵਿਕਾਸ ਦੇ ਵਾਤਾਵਰਣ ਨੂੰ ਸੈਟਅੱਪ ਕਰੋ](./lessons/0-course-setup/how-to-run.md) | |
| 0 | [ਕੋਰਸ ਸੈਟਅਪ](./lessons/0-course-setup/setup.md) | [ਆਪਣੇ ਵਿਕਾਸ ਵਾਤਾਵਰਣ ਨੂੰ ਸੈਟਅਪ ਕਰੋ](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI ਦਾ ਪਰਿਚਯ**](./lessons/1-Intro/README.md) | | |
| 01 | [AI ਦਾ ਪਰਿਚਯ ਅਤੇ ਇਤਿਹਾਸ](./lessons/1-Intro/README.md) | - | - |
| 01 | [AI ਦਾ ਇਤਿਹਾਸ ਅਤੇ ਪਰਿਚਯ](./lessons/1-Intro/README.md) | - | - |
| II | **ਪ੍ਰਤੀਕਾਤਮਕ AI** |
| 02 | [ਗਿਆਨ ਪ੍ਰਸਤੁਤੀ ਅਤੇ ਵਿਸ਼ੇਸ਼ਗਿਆਨ ਪ੍ਰਣਾਲੀਆਂ](./lessons/2-Symbolic/README.md) | [ਵਿਸ਼ੇਸ਼ਗਿਆਨ ਪ੍ਰਣਾਲੀਆਂ](./lessons/2-Symbolic/Animals.ipynb) / [ਓਨਟੋਲੋਜੀ](./lessons/2-Symbolic/FamilyOntology.ipynb) /[ਸੰਕਲਪ ਗ੍ਰਾਫ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**ਨਿਊਰਲ ਨੈੱਟਵਰਕਸ ਦਾ ਪਰਿਚਯ**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [ਪਰਸੈਪਟਰਾਨ](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [ਨੋਟਬੁੱਕ](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [ਪ੍ਰਯੋਗਸ਼ਾਲਾ](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [ਮਲਟੀ-ਲੇਅਰਡ ਪਰਸੈਪਟਰਾਨ ਅਤੇ ਆਪਣਾ ਫਰੇਮਵਰਕ ਬਣਾਉਣਾ](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [ਨੋਟਬੁੱਕ](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [ਪ੍ਰਯੋਗਸ਼ਾਲਾ](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Frameworks (PyTorch/TensorFlow) ਅਤੇ Overfitting ਦਾ ਪਰਚੇ](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**ਕੰਪਿਊਟਰ ਵਿਜ਼ਨ**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure 'ਤੇ ਕੰਪਿਊਟਰ ਵਿਜ਼ਨ ਦੀ ਖੋਜ ਕਰੋ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [ਕੰਪਿਊਟਰ ਵਿਜ਼ਨ ਦਾ ਪਰਚੇ. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Convolutional Neural Networks](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN Architectures](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Pre-trained Networks ਅਤੇ Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) ਅਤੇ [Training Tricks](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoders ਅਤੇ VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generative Adversarial Networks ਅਤੇ Artistic Style Transfer](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Object Detection](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantic Segmentation. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure 'ਤੇ Natural Language Processing ਦੀ ਖੋਜ ਕਰੋ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Text Representation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantic word embeddings. Word2Vec ਅਤੇ GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Language Modeling. ਆਪਣੇ embeddings ਨੂੰ train ਕਰੋ](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Large Language Models, Prompt Programming ਅਤੇ Few-Shot Tasks](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 02 | [ਗਿਆਨ ਪ੍ਰਤੀਨਿਧੀ ਅਤੇ ਵਿਸ਼ੇਸ਼ਗਿਆਨ ਸਿਸਟਮ](./lessons/2-Symbolic/README.md) | [ਵਿਸ਼ੇਸ਼ਗਿਆਨ ਸਿਸਟਮ](./lessons/2-Symbolic/Animals.ipynb) / [Ontology](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Concept Graph](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**ਨਿਊਰਲ ਨੈਟਵਰਕਸ ਦਾ ਪਰਿਚਯ**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [ਪਰਸੈਪਟ੍ਰਾਨ](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [ਨੋਟਬੁੱਕ](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [ਪ੍ਰਯੋਗਸ਼ਾਲਾ](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [ਮਲਟੀ-ਲੇਅਰਡ ਪਰਸੈਪਟ੍ਰਾਨ ਅਤੇ ਆਪਣਾ ਫਰੇਮਵਰਕ ਬਣਾਉਣਾ](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [ਨੋਟਬੁੱਕ](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [ਪ੍ਰਯੋਗਸ਼ਾਲਾ](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [ਫ੍ਰੇਮਵਰਕਸ (PyTorch/TensorFlow) ਅਤੇ ਓਵਰਫਿਟਿੰਗ ਦਾ ਪਰਿਚਯ](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [ਲੈਬ](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**ਕੰਪਿਊਟਰ ਵਿਜ਼ਨ**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [ਮਾਈਕਰੋਸਾਫਟ ਐਜ਼ਿਊਰ 'ਤੇ ਕੰਪਿਊਟਰ ਵਿਜ਼ਨ ਦੀ ਖੋਜ ਕਰੋ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [ਕੰਪਿਊਟਰ ਵਿਜ਼ਨ ਦਾ ਪਰਿਚਯ। OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [ਨੋਟਬੁੱਕ](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [ਲੈਬ](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [ਕੰਵੋਲੂਸ਼ਨਲ ਨਿਊਰਲ ਨੈਟਵਰਕਸ](./lessons/4-ComputerVision/07-ConvNets/README.md) ਅਤੇ [CNN ਆਰਕੀਟੈਕਚਰ](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [ਲੈਬ](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [ਪ੍ਰੀ-ਟ੍ਰੇਨਡ ਨੈਟਵਰਕਸ ਅਤੇ ਟ੍ਰਾਂਸਫਰ ਲਰਨਿੰਗ](./lessons/4-ComputerVision/08-TransferLearning/README.md) ਅਤੇ [ਟ੍ਰੇਨਿੰਗ ਟ੍ਰਿਕਸ](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [ਲੈਬ](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [ਆਟੋਇੰਕੋਡਰ ਅਤੇ VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [ਜਨਰੇਟਿਵ ਐਡਵਰਸਰੀਅਲ ਨੈਟਵਰਕਸ ਅਤੇ ਕਲਾਤਮਿਕ ਸਟਾਈਲ ਟ੍ਰਾਂਸਫਰ](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [ਆਬਜੈਕਟ ਡਿਟੈਕਸ਼ਨ](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [ਲੈਬ](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [ਸੈਮੈਂਟਿਕ ਸੈਗਮੈਂਟੇਸ਼ਨ। U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**ਨੈਚਰਲ ਲੈਂਗਵੇਜ ਪ੍ਰੋਸੈਸਿੰਗ**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [ਮਾਈਕਰੋਸਾਫਟ ਐਜ਼ਿਊਰ 'ਤੇ ਨੈਚਰਲ ਲੈਂਗਵੇਜ ਪ੍ਰੋਸੈਸਿੰਗ ਦੀ ਖੋਜ ਕਰੋ](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [ਟੈਕਸਟ ਪ੍ਰਤੀਨਿਧਿਤਾ। Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [ਸੈਮੈਂਟਿਕ ਵਰਡ ਐਮਬੈਡਿੰਗਸ। Word2Vec ਅਤੇ GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [ਲੈਂਗਵੇਜ ਮਾਡਲਿੰਗ। ਆਪਣੇ ਐਮਬੈਡਿੰਗਸ ਟ੍ਰੇਨ ਕਰੋ](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [ਲੈਬ](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [ਰੀਕਰਨਟ ਨਿਊਰਲ ਨੈਟਵਰਕਸ](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [ਜਨਰੇਟਿਵ ਰੀਕਰਨਟ ਨੈਟਵਰਕਸ](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [ਲੈਬ](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ਟ੍ਰਾਂਸਫਾਰਮਰ। BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [ਨੇਮਡ ਐਂਟਿਟੀ ਰਿਕਗਨਿਸ਼ਨ](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [ਲੈਬ](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [ਵੱਡੇ ਭਾਸ਼ਾ ਮਾਡਲ, ਪ੍ਰੌਮਪਟ ਪ੍ਰੋਗਰਾਮਿੰਗ ਅਤੇ ਫਿਊ-ਸ਼ਾਟ ਟਾਸਕਸ](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **ਹੋਰ AI ਤਕਨੀਕਾਂ** || |
| 21 | [Genetic Algorithms](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Deep Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Multi-Agent Systems](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI Ethics** | | |
| 24 | [AI Ethics ਅਤੇ Responsible AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Responsible AI Principles](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Extras** | | |
| 25 | [Multi-Modal Networks, CLIP ਅਤੇ VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 21 | [ਜੈਨੇਟਿਕ ਐਲਗੋਰਿਥਮ](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [ਨੋਟਬੁੱਕ](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [ਡੀਪ ਰੀਇਨਫੋਰਸਮੈਂਟ ਲਰਨਿੰਗ](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [ਲੈਬ](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [ਮਲਟੀ-ਏਜੰਟ ਸਿਸਟਮ](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI ਨੈਤਿਕਤਾ** | | |
| 24 | [AI ਨੈਤਿਕਤਾ ਅਤੇ ਜ਼ਿੰਮੇਵਾਰ AI](./lessons/7-Ethics/README.md) | [ਮਾਈਕਰੋਸਾਫਟ ਲਰਨ: ਜ਼ਿੰਮੇਵਾਰ AI ਸਿਧਾਂਤ](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **ਵਾਧੂ ਸਮੱਗਰੀ** | | |
| 25 | [ਮਲਟੀ-ਮੋਡਲ ਨੈਟਵਰਕਸ, CLIP ਅਤੇ VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [ਨੋਟਬੁੱਕ](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## ਹਰ ਪਾਠ ਵਿੱਚ ਸ਼ਾਮਲ ਹੈ
* ਪੜ੍ਹਨ ਲਈ ਪਹਿਲਾਂ ਦਾ ਸਮੱਗਰੀ
* ਚਲਾਉਣ ਯੋਗ Jupyter Notebooks, ਜੋ ਅਕਸਰ framework (**PyTorch** ਜਾਂ **TensorFlow**) ਲਈ ਵਿਸ਼ੇਸ਼ ਹੁੰਦੇ ਹਨ। ਚਲਾਉਣ ਯੋਗ notebook ਵਿੱਚ ਬਹੁਤ ਸਾਰਾ ਸਿਧਾਂਤਕ ਸਮੱਗਰੀ ਵੀ ਹੁੰਦੀ ਹੈ, ਇਸ ਲਈ ਵਿਸ਼ੇ ਨੂੰ ਸਮਝਣ ਲਈ ਤੁਹਾਨੂੰ ਘੱਟੋ-ਘੱਟ ਇੱਕ notebook ਦਾ ਵਰਜਨ (PyTorch ਜਾਂ TensorFlow) ਦੇਖਣਾ ਪਵੇਗਾ।
* **Labs** ਕੁਝ ਵਿਸ਼ਿਆਂ ਲਈ ਉਪਲਬਧ ਹਨ, ਜੋ ਤੁਹਾਨੂੰ ਸਿੱਖੀ ਗਈ ਸਮੱਗਰੀ ਨੂੰ ਕਿਸੇ ਵਿਸ਼ੇਸ਼ ਸਮੱਸਿਆ 'ਤੇ ਲਾਗੂ ਕਰਨ ਦਾ ਮੌਕਾ ਦਿੰਦੇ ਹਨ।
* ਕੁਝ ਭਾਗਾਂ ਵਿੱਚ [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) modules ਦੇ ਲਿੰਕ ਸ਼ਾਮਲ ਹਨ ਜੋ ਸੰਬੰਧਿਤ ਵਿਸ਼ਿਆਂ ਨੂੰ ਕਵਰ ਕਰਦੇ ਹਨ।
* ਪੜ੍ਹਨ ਲਈ ਪਹਿਲਾਂ ਦੀ ਸਮੱਗਰੀ
* ਚਲਣਯੋਗ Jupyter ਨੋਟਬੁੱਕਸ, ਜੋ ਅਕਸਰ ਫ੍ਰੇਮਵਰਕ (**PyTorch** ਜਾਂ **TensorFlow**) ਲਈ ਵਿਸ਼ੇਸ਼ ਹੁੰਦੀਆਂ ਹਨ। ਚਲਣਯੋਗ ਨੋਟਬੁੱਕ ਵਿੱਚ ਬਹੁਤ ਸਾਰਾ ਸਿਧਾਂਤਕ ਸਮੱਗਰੀ ਵੀ ਹੁੰਦੀ ਹੈ, ਇਸ ਲਈ ਵਿਸ਼ੇ ਨੂੰ ਸਮਝਣ ਲਈ ਤੁਹਾਨੂੰ ਘੱਟੋ-ਘੱਟ ਨੋਟਬੁੱਕ ਦੇ ਇੱਕ ਸੰਸਕਰਣ (PyTorch ਜਾਂ TensorFlow) ਨੂੰ ਪੜ੍ਹਨਾ ਪਵੇਗਾ।
* ਕੁਝ ਵਿਸ਼ਿਆਂ ਲਈ ਉਪਲਬਧ **ਲੈਬਸ**, ਜੋ ਤੁਹਾਨੂੰ ਸਿੱਖੀ ਸਮੱਗਰੀ ਨੂੰ ਕਿਸੇ ਖਾਸ ਸਮੱਸਿਆ 'ਤੇ ਲਾਗੂ ਕਰਨ ਦਾ ਮੌਕਾ ਦਿੰਦੇ ਹਨ।
* ਕੁਝ ਭਾਗਾਂ ਵਿੱਚ [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) ਮੌਡਿਊਲਾਂ ਦੇ ਲਿੰਕ ਸ਼ਾਮਲ ਹਨ ਜੋ ਸੰਬੰਧਿਤ ਵਿਸ਼ਿਆਂ ਨੂੰ ਕਵਰ ਕਰਦੇ ਹਨ।
## ਸ਼ੁਰੂਆਤ ਕਰਨਾ
- ਅਸੀਂ ਤੁਹਾਡੇ ਵਿਕਾਸ ਦੇ ਮਾਹੌਲ ਨੂੰ ਸੈਟਅੱਪ ਕਰਨ ਵਿੱਚ ਮਦਦ ਕਰਨ ਲਈ ਇੱਕ [setup lesson](./lessons/0-course-setup/setup.md) ਬਣਾਇਆ ਹੈ। - ਸ਼ਿਕਸ਼ਕਾਂ ਲਈ, ਅਸੀਂ ਤੁਹਾਡੇ ਲਈ ਇੱਕ [curricula setup lesson](./lessons/0-course-setup/for-teachers.md) ਵੀ ਬਣਾਇਆ ਹੈ!
- [VSCode ਜਾਂ Codepace ਵਿੱਚ ਕੋਡ ਨੂੰ ਚਲਾਉਣ ਦਾ ਤਰੀਕਾ](./lessons/0-course-setup/how-to-run.md)
- ਅਸੀਂ ਤੁਹਾਡੀ ਡਿਵੈਲਪਮੈਂਟ ਵਾਤਾਵਰਣ ਸੈਟਅੱਪ ਕਰਨ ਵਿੱਚ ਮਦਦ ਕਰਨ ਲਈ ਇੱਕ [ਸੈਟਅੱਪ ਪਾਠ](./lessons/0-course-setup/setup.md) ਬਣਾਇਆ ਹੈ।
- ਸਿੱਖਿਆਕਾਰਾਂ ਲਈ, ਅਸੀਂ ਤੁਹਾਡੇ ਲਈ ਇੱਕ [ਪਾਠਕ੍ਰਮ ਸੈਟਅੱਪ ਪਾਠ](./lessons/0-course-setup/for-teachers.md) ਵੀ ਬਣਾਇਆ ਹੈ!
- [ਕੋਡ ਨੂੰ VSCode ਜਾਂ Codepace ਵਿੱਚ ਕਿਵੇਂ ਚਲਾਉਣਾ ਹੈ](./lessons/0-course-setup/how-to-run.md)
ਇਹ ਕਦਮਾਂ ਦੀ ਪਾਲਣਾ ਕਰੋ:
ਇਹ ਕਦਮ ਫੋਲੋ ਕਰੋ:
Repository ਨੂੰ Fork ਕਰੋ: ਇਸ ਪੰਨੇ ਦੇ ਸਿਖਰ-ਦਾਖਣੇ 'Fork' ਬਟਨ 'ਤੇ ਕਲਿਕ ਕਰੋ।
ਰਿਪੋਜ਼ਟਰੀ ਨੂੰ ਫੋਰਕ ਕਰੋ: ਇਸ ਪੰਨੇ ਦੇ ਸੱਜੇ-ਉੱਪਰਲੇ ਕੋਨੇ 'ਤੇ "Fork" ਬਟਨ 'ਤੇ ਕਲਿਕ ਕਰੋ।
Repository ਨੂੰ Clone ਕਰੋ: `git clone https://github.com/microsoft/AI-For-Beginners.git`
ਰਿਪੋਜ਼ਟਰੀ ਨੂੰ ਕਲੋਨ ਕਰੋ: `git clone https://github.com/microsoft/AI-For-Beginners.git`
ਇਸ repo ਨੂੰ ਬਾਅਦ ਵਿੱਚ ਆਸਾਨੀ ਨਾਲ ਲੱਭਣ ਲਈ ਇਸ ਨੂੰ star (🌟) ਕਰਨਾ ਨਾ ਭੁੱਲੋ।
ਇਸ ਰਿਪੋ ਨੂੰ ਬਾਅਦ ਵਿੱਚ ਆਸਾਨੀ ਨਾਲ ਲੱਭਣ ਲਈ ਇਸਨੂੰ ਸਟਾਰ (🌟) ਕਰਨਾ ਨਾ ਭੁੱਲੋ।
## ਹੋਰ ਸਿੱਖਣ ਵਾਲਿਆਂ ਨੂੰ ਮਿਲੋ
## ਹੋਰ ਸਿੱਖਣ ਵਾਲਿਆਂ ਨਾਲ ਮਿਲੋ
ਸਾਡੇ [official AI Discord server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) ਵਿੱਚ ਸ਼ਾਮਲ ਹੋਵੋ ਤਾਂ ਜੋ ਇਸ ਕੋਰਸ ਨੂੰ ਲੈਣ ਵਾਲੇ ਹੋਰ ਸਿੱਖਣ ਵਾਲਿਆਂ ਨਾਲ ਮਿਲ ਸਕੋ ਅਤੇ ਸਹਾਇਤਾ ਪ੍ਰਾਪਤ ਕਰ ਸਕੋ।
ਸਾਡੇ [ਆਧਿਕਾਰਿਕ AI ਡਿਸਕੋਰਡ ਸਰਵਰ](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) ਵਿੱਚ ਸ਼ਾਮਲ ਹੋਵੋ ਤਾਂ ਜੋ ਇਸ ਕੋਰਸ ਨੂੰ ਕਰਨ ਵਾਲੇ ਹੋਰ ਸਿੱਖਣ ਵਾਲਿਆਂ ਨਾਲ ਮਿਲ ਸਕੋ ਅਤੇ ਸਹਾਇਤਾ ਪ੍ਰਾਪਤ ਕਰ ਸਕੋ।
ਜੇ ਤੁਹਾਡੇ ਕੋਲ ਉਤਪਾਦ ਫੀਡਬੈਕ ਹੈ ਜਾਂ ਬਣਾਉਣ ਦੌਰਾਨ ਸਵਾਲ ਹਨ ਤਾਂ ਸਾਡੇ [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) 'ਤੇ ਜਾਓ।
ਜੇ ਤੁਹਾਡੇ ਕੋਲ ਉਤਪਾਦ ਫੀਡਬੈਕ ਹੈ ਜਾਂ ਬਿਲਡਿੰਗ ਦੌਰਾਨ ਸਵਾਲ ਹਨ ਤਾਂ ਸਾਡੇ [ਐਜ਼ਿਊਰ AI ਫਾਉਂਡਰੀ ਡਿਵੈਲਪਰ ਫੋਰਮ](https://aka.ms/foundry/forum) 'ਤੇ ਜਾਓ।
## ਪ੍ਰਸ਼ਨ
## ਪ੍ਰਸ਼ਨੋੱਤਰੀ
> **ਕੁਇਜ਼ਾਂ ਬਾਰੇ ਇੱਕ ਨੋਟ**: ਸਾਰੀਆਂ ਕੁਇਜ਼ਾਂ Quiz-app ਫੋਲਡਰ ਵਿੱਚ etc\quiz-app ਵਿੱਚ ਸ਼ਾਮਲ ਹਨ, ਜਾਂ [Online Here](https://ff-quizzes.netlify.app/)। ਇਹ ਪਾਠਾਂ ਵਿੱਚੋਂ ਲਿੰਕ ਕੀਤੀਆਂ ਗਈਆਂ ਹਨ। ਕੁਇਜ਼ ਐਪ ਨੂੰ ਸਥਾਨਕ ਤੌਰ 'ਤੇ ਚਲਾਇਆ ਜਾ ਸਕਦਾ ਹੈ ਜਾਂ Azure 'ਤੇ ਡਿਪਲੌਇ ਕੀਤਾ ਜਾ ਸਕਦਾ ਹੈ; `quiz-app` ਫੋਲਡਰ ਵਿੱਚ ਦਿੱਤੇ ਨਿਰਦੇਸ਼ਾਂ ਦੀ ਪਾਲਣਾ ਕਰੋ। ਇਹ ਹੌਲੀ-ਹੌਲੀ ਸਥਾਨਕ ਭਾਸ਼ਾਵਾਂ ਵਿੱਚ ਅਨੁਵਾਦਿਤ ਕੀਤੀਆਂ ਜਾ ਰਹੀਆਂ ਹਨ।
## ਮਦਦ ਦੀ ਲੋੜ
## ਮਦਦ ਦੀ ਲੋੜ ਹੈ
ਕੀ ਤੁਹਾਡੇ ਕੋਲ ਸੁਝਾਵ ਹਨ ਜਾਂ ਤੁਸੀਂ ਕੋਈ ਸ਼ਬਦ ਜਾਂ ਕੋਡ ਦੀ ਗਲਤੀ ਲੱਭੀ ਹੈ? ਇੱਕ ਇਸ਼ੂ ਰੇਜ਼ ਕਰੋ ਜਾਂ ਪੁਲ ਰਿਕਵੈਸਟ ਬਣਾਓ।
ਕੀ ਤੁਹਾਡੇ ਕੋਲ ਸੁਝਾਅ ਹਨ ਜਾਂ ਤੁਸੀਂ ਕੋਈ ਹਿਪਤੀਆਂ ਜਾਂ ਕੋਡ ਦੀਆਂ ਗਲਤੀਆਂ ਲੱਭੀਆਂ ਹਨ? ਇੱਕ ਇਸ਼ੂ ਰੇਜ਼ ਕਰੋ ਜਾਂ ਪੁਲ ਰਿਕਵੇਸਟ ਬਣਾਓ।
## ਖਾਸ ਧੰਨਵਾਦ
## ਵਿਸ਼ੇਸ਼ ਧੰਨਵਾਦ
* **✍️ ਮੁੱਖ ਲੇਖਕ:** [ਦਿਮਿਤਰੀ ਸੋਸ਼ਨਿਕੋਵ](http://soshnikov.com), ਪੀਐਚਡੀ
* **🔥 ਸੰਪਾਦਕ:** [ਜੈਨ ਲੂਪਰ](https://twitter.com/jenlooper), ਪੀਐਚਡੀ
* **🎨 ਸਕੈਚਨੋਟ ਇਲਸਟਰੇਟਰ:** [ਤੋਮੋਮੀ ਇਮੁਰਾ](https://twitter.com/girlie_mac)
* **✅ ਕਵਿਜ਼ ਬਣਾਉਣ ਵਾਲਾ:** [ਲਤੀਫਾ ਬੇਲੋ](https://github.com/CinnamonXI), [ਐਮਐਲਐਸਏ](https://studentambassadors.microsoft.com/)
* **🙏 ਮੁੱਖ ਯੋਗਦਾਨਕਰਤਾ:** [ਏਵਗੇਨੀ ਪਿਸ਼ਚਿਕ](https://github.com/Pe4enIks)
* **✍️ ਮੁੱਖ ਲੇਖਕ:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 ਸੰਪਾਦਕ:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 ਸਕੈਚਨੋਟ ਇਲਸਟ੍ਰੇਟਰ:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ ਕਵਿਜ ਬਣਾਉਣ ਵਾਲਾ:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 ਮੁੱਖ ਯੋਗਦਾਨਕਰਤਾ:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## ਹੋਰ ਪਾਠਕ੍ਰਮ
ਸਾਡੀ ਟੀਮ ਹੋਰ ਪਾਠਕ੍ਰਮ ਵੀ ਤਿਆਰ ਕਰਦੀ ਹੈ! ਜ਼ਰੂਰ ਦੇਖੋ:
ਸਾਡੀ ਟੀਮ ਹੋਰ ਪਾਠਕ੍ਰਮ ਤਿਆਰ ਕਰਦੀ ਹੈ! ਜਾਚ ਕਰੋ:
- [ਸ਼ੁਰੂਆਤੀ ਲਈ ਜਨਰੇਟਿਵ AI](https://aka.ms/genai-beginners)
- [ਸ਼ੁਰੂਆਤੀ ਲਈ ਜਨਰੇਟਿਵ AI .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [ਜਾਵਾਸਕ੍ਰਿਪਟ ਨਾਲ ਜਨਰੇਟਿਵ AI](https://github.com/microsoft/generative-ai-with-javascript)
- [ਜਾਵਾ ਨਾਲ ਜਨਰੇਟਿਵ AI](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [ਸ਼ੁਰੂਆਤੀ ਲਈ AI](https://aka.ms/ai-beginners)
- [ਸ਼ੁਰੂਆਤੀ ਲਈ ਡਾਟਾ ਸਾਇੰਸ](https://aka.ms/datascience-beginners)
- [ਸ਼ੁਰੂਆਤੀ ਲਈ ਮਸ਼ੀਨ ਲਰਨਿੰਗ](https://aka.ms/ml-beginners)
- [ਸ਼ੁਰੂਆਤੀ ਲਈ ਸਾਇਬਰਸੁਰੱਖਿਆ](https://github.com/microsoft/Security-101)
- [ਸ਼ੁਰੂਆਤੀ ਲਈ ਵੈੱਬ ਡਿਵੈਲਪਮੈਂਟ](https://aka.ms/webdev-beginners)
- [ਸ਼ੁਰੂਆਤੀ ਲਈ IoT](https://aka.ms/iot-beginners)
- [ਸ਼ੁਰੂਆਤੀ ਲਈ XR ਡਿਵੈਲਪਮੈਂਟ](https://github.com/microsoft/xr-development-for-beginners)
- [ਏਜੈਂਟਿਕ ਵਰਤੋਂ ਲਈ GitHub Copilot ਵਿੱਚ ਨਿਪੁੰਨਤਾ](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [C#/.NET ਡਿਵੈਲਪਰਾਂ ਲਈ GitHub Copilot ਵਿੱਚ ਨਿਪੁੰਨਤਾ](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [ਆਪਣੇ ਆਪ ਦੀ Copilot ਐਡਵੈਂਚਰ ਚੁਣੋ](https://github.com/microsoft/CopilotAdventures)
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---
**ਅਸਵੀਕਰਤੀ**:
ਇਹ ਦਸਤਾਵੇਜ਼ AI ਅਨੁਵਾਦ ਸੇਵਾ [Co-op Translator](https://github.com/Azure/co-op-translator) ਦੀ ਵਰਤੋਂ ਕਰਕੇ ਅਨੁਵਾਦ ਕੀਤਾ ਗਿਆ ਹੈ। ਜਦੋਂ ਕਿ ਅਸੀਂ ਸਹੀ ਹੋਣ ਦਾ ਯਤਨ ਕਰਦੇ ਹਾਂ, ਕਿਰਪਾ ਕਰਕੇ ਧਿਆਨ ਦਿਓ ਕਿ ਸਵੈਚਾਲਿਤ ਅਨੁਵਾਦਾਂ ਵਿੱਚ ਗਲਤੀਆਂ ਜਾਂ ਅਸੁੱਤੀਆਂ ਹੋ ਸਕਦੀਆਂ ਹਨ। ਇਸ ਦੀ ਮੂਲ ਭਾਸ਼ਾ ਵਿੱਚ ਮੌਜੂਦ ਮੂਲ ਦਸਤਾਵੇਜ਼ ਨੂੰ ਪ੍ਰਮਾਣਿਕ ਸਰੋਤ ਮੰਨਿਆ ਜਾਣਾ ਚਾਹੀਦਾ ਹੈ। ਮਹੱਤਵਪੂਰਨ ਜਾਣਕਾਰੀ ਲਈ, ਪੇਸ਼ੇਵਰ ਮਨੁੱਖੀ ਅਨੁਵਾਦ ਦੀ ਸਿਫਾਰਸ਼ ਕੀਤੀ ਜਾਂਦੀ ਹੈ। ਇਸ ਅਨੁਵਾਦ ਦੇ ਪ੍ਰਯੋਗ ਤੋਂ ਪੈਦਾ ਹੋਣ ਵਾਲੇ ਕਿਸੇ ਵੀ ਗਲਤਫਹਮੀ ਜਾਂ ਗਲਤ ਵਿਆਖਿਆ ਲਈ ਅਸੀਂ ਜ਼ਿੰਮੇਵਾਰ ਨਹੀਂ ਹਾਂ।
**ਅਸਵੀਕਤੀ**:
ਇਹ ਦਸਤਾਵੇਜ਼ AI ਅਨੁਵਾਦ ਸੇਵਾ [Co-op Translator](https://github.com/Azure/co-op-translator) ਦੀ ਵਰਤੋਂ ਕਰਕੇ ਅਨੁਵਾਦ ਕੀਤਾ ਗਿਆ ਹੈ। ਜਦੋਂ ਕਿ ਅਸੀਂ ਸਹੀਤਾ ਲਈ ਯਤਨਸ਼ੀਲ ਹਾਂ, ਕਿਰਪਾ ਕਰਕੇ ਧਿਆਨ ਦਿਓ ਕਿ ਸਵੈਚਾਲਿਤ ਅਨੁਵਾਦਾਂ ਵਿੱਚ ਗਲਤੀਆਂ ਜਾਂ ਅਸੁਚਨਾਵਾਂ ਹੋ ਸਕਦੀਆਂ ਹਨ। ਇਸ ਦਸਤਾਵੇਜ਼ ਦਾ ਮੂਲ ਰੂਪ ਇਸਦੀ ਮੂਲ ਭਾਸ਼ਾ ਵਿੱਚ ਅਧਿਕਾਰਤ ਸਰੋਤ ਮੰਨਿਆ ਜਾਣਾ ਚਾਹੀਦਾ ਹੈ। ਮਹੱਤਵਪੂਰਨ ਜਾਣਕਾਰੀ ਲਈ, ਪੇਸ਼ੇਵਰ ਮਨੁੱਖੀ ਅਨੁਵਾਦ ਦੀ ਸਿਫਾਰਸ਼ ਕੀਤੀ ਜਾਂਦੀ ਹੈ। ਇਸ ਅਨੁਵਾਦ ਦੀ ਵਰਤੋਂ ਤੋਂ ਪੈਦਾ ਹੋਣ ਵਾਲੇ ਕਿਸੇ ਵੀ ਗਲਤਫਹਿਮੀ ਜਾਂ ਗਲਤ ਵਿਆਖਿਆ ਲਈ ਅਸੀਂ ਜ਼ਿੰਮੇਵਾਰ ਨਹੀਂ ਹਾਂ।

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@ -1,8 +1,8 @@
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@ -23,7 +23,7 @@ CO_OP_TRANSLATOR_METADATA:
# Sztuczna Inteligencja dla Początkujących - Program Nauczania
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.pl.png)|
|:---:|
| AI For Beginners - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ |
@ -59,7 +59,7 @@ Czego nie obejmuje ten program nauczania:
* **Klasycznego Uczenia Maszynowego**, które jest dobrze opisane w naszym [Programie Nauczania Uczenia Maszynowego dla Początkujących](http://github.com/Microsoft/ML-for-Beginners).
* Praktycznych zastosowań AI zbudowanych przy użyciu **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. W tym celu zalecamy rozpoczęcie od modułów Microsoft Learn dla [wizji komputerowej](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [przetwarzania języka naturalnego](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** i innych.
* Specyficznych **Cloud Frameworks** dla ML, takich jak [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) czy [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Rozważ skorzystanie z ścieżek nauczania [Budowanie i operowanie rozwiązaniami uczenia maszynowego z Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) oraz [Budowanie i operowanie rozwiązaniami uczenia maszynowego z Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Konwersacyjnej AI** i **Chatbotów**. Istnieje osobna ścieżka nauczania [Tworzenie rozwiązań konwersacyjnej AI](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), a także możesz zapoznać się z [tym wpisem na blogu](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) dla bardziej szczegółowych informacji.
* **Konwersacyjnej AI** i **Chat Botów**. Istnieje osobna ścieżka nauczania [Tworzenie rozwiązań konwersacyjnej AI](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), a także możesz zapoznać się z [tym wpisem na blogu](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) dla bardziej szczegółowych informacji.
* **Zaawansowanej matematyki** stojącej za głębokim uczeniem. W tym celu polecamy książkę [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) autorstwa Iana Goodfellowa, Yoshuy Bengio i Aarona Courville, która jest również dostępna online pod adresem [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Dla łagodnego wprowadzenia do tematów związanych z _AI w chmurze_ możesz rozważyć skorzystanie z ścieżki nauczania [Rozpocznij pracę ze sztuczną inteligencją na Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
@ -76,93 +76,93 @@ Dla łagodnego wprowadzenia do tematów związanych z _AI w chmurze_ możesz roz
| III | [**Wprowadzenie do sieci neuronowych**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Laboratorium](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Wielowarstwowy perceptron i tworzenie własnego frameworka](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Laboratorium](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Wprowadzenie do Frameworków (PyTorch/TensorFlow) i Przeuczenia](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Wizja Komputerowa**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Poznaj Wizję Komputerową na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Wprowadzenie do Wizji Komputerowej. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Splotowe Sieci Neuronowe](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Architektury CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Sieci Wstępnie Wytrenowane i Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) oraz [Triki Treningowe](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 05 | [Wprowadzenie do Frameworków (PyTorch/TensorFlow) i Przeuczenia](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorium](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Wizja Komputerowa**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Odkryj Wizję Komputerową na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Wprowadzenie do Wizji Komputerowej. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Laboratorium](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konwolucyjne Sieci Neuronowe](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Architektury CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Laboratorium](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Sieci wstępnie wytrenowane i Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) oraz [Triki treningowe](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorium](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoenkodery i VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generatywne Sieci Adwersyjne i Transfer Stylu Artystycznego](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Detekcja Obiektów](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 10 | [Generatywne Sieci Adwersarialne i Transfer Stylu Artystycznego](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Detekcja Obiektów](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Laboratorium](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Segmentacja Semantyczna. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Przetwarzanie Języka Naturalnego**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Poznaj Przetwarzanie Języka Naturalnego na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Reprezentacja Tekstu. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantyczne Wektory Słów. Word2Vec i GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelowanie Języka. Trening Własnych Wektorów](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurencyjne Sieci Neuronowe](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatywne Sieci Rekurencyjne](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformery. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Rozpoznawanie Nazwanych Jednostek](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Duże Modele Językowe, Programowanie z Wykorzystaniem Podpowiedzi i Zadania Few-Shot](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Inne Techniki Sztucznej Inteligencji** || |
| V | [**Przetwarzanie Języka Naturalnego**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Odkryj Przetwarzanie Języka Naturalnego na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Reprezentacja Tekstu. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantyczne osadzenia słów. Word2Vec i GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelowanie Języka. Trening własnych osadzeń](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratorium](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurencyjne Sieci Neuronowe](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatywne Sieci Rekurencyjne](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Laboratorium](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformery. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Rozpoznawanie Nazwanych Jednostek](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratorium](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Duże Modele Językowe, Programowanie Podpowiedzi i Zadania Few-Shot](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Inne Techniki AI** || |
| 21 | [Algorytmy Genetyczne](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Głębokie Uczenie Wzmocnione](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 22 | [Głębokie Uczenie Wzmocnione](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Laboratorium](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Systemy Wieloagentowe](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Etyka Sztucznej Inteligencji** | | |
| 24 | [Etyka Sztucznej Inteligencji i Odpowiedzialna AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Zasady Odpowiedzialnej AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| VII | **Etyka AI** | | |
| 24 | [Etyka AI i Odpowiedzialna AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Zasady Odpowiedzialnej AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Dodatki** | | |
| 25 | [Sieci Multi-Modalne, CLIP i VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Każda lekcja zawiera
* Materiały do przeczytania przed zajęciami
* Wykonywalne notatniki Jupyter, często specyficzne dla danego frameworka (**PyTorch** lub **TensorFlow**). Notatniki zawierają również dużo materiału teoretycznego, więc aby zrozumieć temat, należy przejść przez przynajmniej jedną wersję notatnika (PyTorch lub TensorFlow).
* **Lab** dostępne dla niektórych tematów, które dają możliwość zastosowania zdobytej wiedzy w praktyce.
* Materiały wstępne do przeczytania
* Wykonywalne Notatniki Jupyter, często specyficzne dla danego frameworka (**PyTorch** lub **TensorFlow**). Wykonywalny notatnik zawiera również dużo materiału teoretycznego, więc aby zrozumieć temat, należy przejść przez co najmniej jedną wersję notatnika (PyTorch lub TensorFlow).
* **Laboratoria** dostępne dla niektórych tematów, które dają możliwość zastosowania zdobytej wiedzy do konkretnego problemu.
* Niektóre sekcje zawierają linki do modułów [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum), które obejmują powiązane tematy.
## Rozpoczęcie
- Przygotowaliśmy [lekcję wprowadzającą](./lessons/0-course-setup/setup.md), która pomoże Ci skonfigurować środowisko programistyczne. - Dla nauczycieli stworzyliśmy również [lekcję dotyczącą przygotowania programu nauczania](./lessons/0-course-setup/for-teachers.md)!
- Przygotowaliśmy [lekcję wprowadzającą](./lessons/0-course-setup/setup.md), która pomoże Ci skonfigurować środowisko programistyczne. - Dla nauczycieli przygotowaliśmy również [lekcję dotyczącą programu nauczania](./lessons/0-course-setup/for-teachers.md)!
- Jak [Uruchomić kod w VSCode lub Codepace](./lessons/0-course-setup/how-to-run.md)
Wykonaj następujące kroki:
Postępuj zgodnie z tymi krokami:
Sforkuj repozytorium: Kliknij przycisk "Fork" w prawym górnym rogu tej strony.
Forkuj Repozytorium: Kliknij przycisk "Fork" w prawym górnym rogu tej strony.
Sklonuj repozytorium: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Sklonuj Repozytorium: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Nie zapomnij dodać gwiazdki (🌟) temu repozytorium, aby łatwiej je znaleźć później.
Nie zapomnij oznaczyć gwiazdką (🌟) tego repozytorium, aby łatwiej je znaleźć później.
## Poznaj innych uczących się
## Poznaj innych Uczestników
Dołącz do naszego [oficjalnego serwera Discord AI](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), aby poznać i nawiązać kontakt z innymi uczestnikami kursu oraz uzyskać wsparcie.
Dołącz do naszego [oficjalnego serwera AI na Discordzie](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), aby spotkać się i nawiązać kontakty z innymi uczestnikami kursu oraz uzyskać wsparcie.
Jeśli masz uwagi dotyczące produktu lub pytania podczas pracy, odwiedź nasze [Forum Deweloperów Azure AI Foundry](https://aka.ms/foundry/forum)
Jeśli masz uwagi dotyczące produktu lub pytania podczas budowy, odwiedź nasze [Forum dla Programistów Azure AI Foundry](https://aka.ms/foundry/forum)
## Quizy
> **Uwaga dotycząca quizów**: Wszystkie quizy znajdują się w folderze Quiz-app w etc\quiz-app lub [Online tutaj](https://ff-quizzes.netlify.app/). Są one powiązane z lekcjami, a aplikację quizową można uruchomić lokalnie lub wdrożyć na platformie Azure; postępuj zgodnie z instrukcjami w folderze `quiz-app`. Są one stopniowo lokalizowane.
> **Uwaga dotycząca quizów**: Wszystkie quizy znajdują się w folderze Quiz-app w etc\quiz-app, lub [Online tutaj](https://ff-quizzes.netlify.app/). Są one powiązane z lekcjami, aplikacja quizowa może być uruchamiana lokalnie lub wdrażana na Azure; postępuj zgodnie z instrukcjami w folderze `quiz-app`. Są stopniowo lokalizowane.
## Poszukiwani Pomocnicy
Masz sugestie lub znalazłeś błędy w pisowni albo kodzie? Zgłoś problem lub utwórz pull request.
Masz sugestie lub znalazłeś błędy w pisowni albo kodzie? Zgłoś problem lub stwórz pull request.
## Specjalne Podziękowania
* **✍️ Główny Autor:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Redaktor:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustrator sketchnotek:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Twórca quizów:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Główni Współtwórcy:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ Główny Autor:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Redaktor:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustrator sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Twórca quizów:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Główni Współtwórcy:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Inne Programy Nauczania
Nasz zespół tworzy inne programy nauczania! Sprawdź:
- [Generatywna AI dla Początkujących](https://aka.ms/genai-beginners)
- [Generatywna AI dla Początkujących .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generatywna AI z JavaScriptem](https://github.com/microsoft/generative-ai-with-javascript)
- [Generatywna AI z Javą](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI dla Początkujących](https://aka.ms/ai-beginners)
- [Data Science dla Początkujących](https://aka.ms/datascience-beginners)
- [ML dla Początkujących](https://aka.ms/ml-beginners)
- [Cyberbezpieczeństwo dla Początkujących](https://github.com/microsoft/Security-101)
- [Web Dev dla Początkujących](https://aka.ms/webdev-beginners)
- [IoT dla Początkujących](https://aka.ms/iot-beginners)
- [Rozwój XR dla Początkujących](https://github.com/microsoft/xr-development-for-beginners)
- [Opanowanie GitHub Copilot do Agentowego Użycia](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Opanowanie GitHub Copilot dla Programistów C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Wybierz Swoją Własną Przygodę z Copilotem](https://github.com/microsoft/CopilotAdventures)
- [Generatywna AI dla Początkujących](https://aka.ms/genai-beginners)
- [Generatywna AI dla Początkujących .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generatywna AI z JavaScriptem](https://github.com/microsoft/generative-ai-with-javascript)
- [Generatywna AI z Javą](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI dla Początkujących](https://aka.ms/ai-beginners)
- [Data Science dla Początkujących](https://aka.ms/datascience-beginners)
- [ML dla Początkujących](https://aka.ms/ml-beginners)
- [Cyberbezpieczeństwo dla Początkujących](https://github.com/microsoft/Security-101)
- [Web Dev dla Początkujących](https://aka.ms/webdev-beginners)
- [IoT dla Początkujących](https://aka.ms/iot-beginners)
- [Rozwój XR dla Początkujących](https://github.com/microsoft/xr-development-for-beginners)
- [Opanowanie GitHub Copilot do Agentowego Użycia](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Opanowanie GitHub Copilot dla Programistów C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Wybierz Swoją Własną Przygodę z Copilotem](https://github.com/microsoft/CopilotAdventures)
---
**Zastrzeżenie**:
Ten dokument został przetłumaczony za pomocą usługi tłumaczenia AI [Co-op Translator](https://github.com/Azure/co-op-translator). Chociaż dokładamy wszelkich starań, aby tłumaczenie było precyzyjne, prosimy pamiętać, że automatyczne tłumaczenia mogą zawierać błędy lub nieścisłości. Oryginalny dokument w jego rodzimym języku powinien być uznawany za źródło autorytatywne. W przypadku informacji o kluczowym znaczeniu zaleca się skorzystanie z profesjonalnego tłumaczenia przez człowieka. Nie ponosimy odpowiedzialności za jakiekolwiek nieporozumienia lub błędne interpretacje wynikające z użycia tego tłumaczenia.
Ten dokument został przetłumaczony za pomocą usługi tłumaczenia AI [Co-op Translator](https://github.com/Azure/co-op-translator). Chociaż dokładamy wszelkich starań, aby tłumaczenie było precyzyjne, prosimy pamiętać, że automatyczne tłumaczenia mogą zawierać błędy lub nieścisłości. Oryginalny dokument w jego języku źródłowym powinien być uznawany za wiarygodne źródło. W przypadku informacji o kluczowym znaczeniu zaleca się skorzystanie z profesjonalnego tłumaczenia przez człowieka. Nie ponosimy odpowiedzialności za jakiekolwiek nieporozumienia lub błędne interpretacje wynikające z użycia tego tłumaczenia.

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@ -1,8 +1,8 @@
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@ -23,11 +23,11 @@ CO_OP_TRANSLATOR_METADATA:
# Inteligência Artificial para Iniciantes - Um Currículo
|![Sketchnote por @girlie_mac https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|![Sketchnote por @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.pt.png)|
|:---:|
| AI For Beginners - _Sketchnote por [@girlie_mac](https://twitter.com/girlie_mac)_ |
Explore o mundo da **Inteligência Artificial** (IA) com o nosso currículo de 12 semanas e 24 aulas! Inclui lições práticas, questionários e laboratórios. O currículo é adequado para iniciantes e aborda ferramentas como TensorFlow e PyTorch, além de ética na IA.
Explore o mundo da **Inteligência Artificial** (IA) com o nosso currículo de 12 semanas e 24 aulas! Inclui lições práticas, questionários e laboratórios. O currículo é voltado para iniciantes e aborda ferramentas como TensorFlow e PyTorch, além de ética na IA.
### 🌐 Suporte Multilíngue
@ -40,14 +40,14 @@ Explore o mundo da **Inteligência Artificial** (IA) com o nosso currículo de 1
## Junte-se à Comunidade
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## O que irá aprender
## O que você vai aprender
**[Mapa Mental do Curso](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[Mapa mental do curso](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
Neste currículo, irá aprender:
Neste currículo, você aprenderá:
* Diferentes abordagens para Inteligência Artificial, incluindo a abordagem simbólica "tradicional" com **Representação de Conhecimento** e raciocínio ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Redes Neurais** e **Aprendizagem Profunda**, que estão no centro da IA moderna. Vamos ilustrar os conceitos por trás destes tópicos importantes usando código em dois dos frameworks mais populares - [TensorFlow](http://Tensorflow.org) e [PyTorch](http://pytorch.org).
* **Redes Neurais** e **Aprendizagem Profunda**, que estão no centro da IA moderna. Vamos ilustrar os conceitos por trás desses tópicos importantes usando código em dois dos frameworks mais populares - [TensorFlow](http://Tensorflow.org) e [PyTorch](http://pytorch.org).
* **Arquiteturas Neurais** para trabalhar com imagens e texto. Vamos abordar modelos recentes, mas talvez faltem alguns dos mais avançados.
* Abordagens menos populares de IA, como **Algoritmos Genéticos** e **Sistemas Multiagentes**.
@ -55,20 +55,20 @@ O que não será abordado neste currículo:
> [Encontre todos os recursos adicionais para este curso na nossa coleção Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Casos de uso de **IA em Negócios**. Considere fazer o percurso de aprendizagem [Introdução à IA para utilizadores empresariais](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) no Microsoft Learn, ou [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), desenvolvido em cooperação com [INSEAD](https://www.insead.edu/).
* Casos de uso de **IA em Negócios**. Considere fazer o percurso de aprendizagem [Introdução à IA para usuários de negócios](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) no Microsoft Learn, ou [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), desenvolvido em cooperação com [INSEAD](https://www.insead.edu/).
* **Aprendizagem Automática Clássica**, que está bem descrita no nosso [Currículo de Aprendizagem Automática para Iniciantes](http://github.com/Microsoft/ML-for-Beginners).
* Aplicações práticas de IA construídas usando **[Serviços Cognitivos](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Para isso, recomendamos começar com os módulos do Microsoft Learn para [visão](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [processamento de linguagem natural](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[IA Generativa com Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** e outros.
* Frameworks específicos de **ML na Nuvem**, como [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), ou [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Considere usar os percursos de aprendizagem [Construir e operar soluções de aprendizagem automática com Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) e [Construir e operar soluções de aprendizagem automática com Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **IA Conversacional** e **Chat Bots**. Há um percurso de aprendizagem separado [Criar soluções de IA conversacional](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), e também pode consultar [este post no blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) para mais detalhes.
* Frameworks específicos de **ML na Nuvem**, como [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), ou [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Considere usar os percursos de aprendizagem [Construa e opere soluções de aprendizagem automática com Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) e [Construa e opere soluções de aprendizagem automática com Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **IA Conversacional** e **Chat Bots**. Há um percurso de aprendizagem separado [Crie soluções de IA conversacional](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), e você também pode consultar [este post no blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) para mais detalhes.
* **Matemática Avançada** por trás da aprendizagem profunda. Para isso, recomendamos [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) de Ian Goodfellow, Yoshua Bengio e Aaron Courville, que também está disponível online em [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Para uma introdução mais leve aos tópicos de _IA na Nuvem_, pode considerar fazer o percurso de aprendizagem [Introdução à inteligência artificial no Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
Para uma introdução mais leve aos tópicos de _IA na Nuvem_, você pode considerar fazer o percurso de aprendizagem [Introdução à inteligência artificial no Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Conteúdo
| | Link da Aula | PyTorch/Keras/TensorFlow | Laboratório |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Configuração do Curso](./lessons/0-course-setup/setup.md) | [Configurar o Ambiente de Desenvolvimento](./lessons/0-course-setup/how-to-run.md) | |
| 0 | [Configuração do Curso](./lessons/0-course-setup/setup.md) | [Configure o seu Ambiente de Desenvolvimento](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Introdução à IA**](./lessons/1-Intro/README.md) | | |
| 01 | [Introdução e História da IA](./lessons/1-Intro/README.md) | - | - |
| II | **IA Simbólica** |
@ -83,17 +83,17 @@ Para uma introdução mais leve aos tópicos de _IA na Nuvem_, pode considerar f
| 08 | [Redes Pré-treinadas e Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) e [Dicas de Treinamento](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratório](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoders e VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Redes Adversárias Generativas & Transferência de Estilo Artístico](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Deteção de Objetos](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Laboratório](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 11 | [Detecção de Objetos](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Laboratório](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Segmentação Semântica. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Processamento de Linguagem Natural**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Explorar Processamento de Linguagem Natural no Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Representação de Texto. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embeddings Semânticos de Palavras. Word2Vec e GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelagem de Linguagem. Treinando os seus próprios embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratório](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Redes Neuronais Recorrentes](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Redes Recorrentes Generativas](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Laboratório](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Reconhecimento de Entidades Nomeadas](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratório](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Modelos de Linguagem de Grande Escala, Programação de Prompts e Tarefas de Poucos Exemplos](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Representação de Texto. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embeddings Semânticos de Palavras. Word2Vec e GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelagem de Linguagem. Treinando seus próprios embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratório](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Redes Neuronais Recorrentes](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Redes Recorrentes Generativas](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Laboratório](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Reconhecimento de Entidades Nomeadas](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratório](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Modelos de Linguagem Grandes, Programação de Prompts e Tarefas de Poucos Exemplos](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Outras Técnicas de IA** || |
| 21 | [Algoritmos Genéticos](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Aprendizagem por Reforço Profundo](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Laboratório](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -105,16 +105,15 @@ Para uma introdução mais leve aos tópicos de _IA na Nuvem_, pode considerar f
## Cada lição contém
* Material de leitura prévia
* Notebooks Jupyter executáveis, muitas vezes específicos para o framework (**PyTorch** ou **TensorFlow**). O notebook executável também contém muito material teórico, por isso, para compreender o tópico, é necessário passar por pelo menos uma versão do notebook (seja PyTorch ou TensorFlow).
* **Laboratórios** disponíveis para alguns tópicos, que oferecem a oportunidade de aplicar o material aprendido a um problema específico.
* Algumas secções contêm links para módulos do [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) que abordam tópicos relacionados.
* Material de leitura prévia
* Jupyter Notebooks executáveis, que frequentemente são específicos para o framework (**PyTorch** ou **TensorFlow**). O notebook executável também contém muito material teórico, então para entender o tópico é necessário passar por pelo menos uma versão do notebook (PyTorch ou TensorFlow).
* **Laboratórios** disponíveis para alguns tópicos, que oferecem a oportunidade de aplicar o material aprendido a um problema específico.
* Algumas seções contêm links para módulos do [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) que abordam tópicos relacionados.
## Começar
## Começando
- Criámos uma [lição de configuração](./lessons/0-course-setup/setup.md) para ajudar a configurar o seu ambiente de desenvolvimento.
- Para Educadores, criámos uma [lição de configuração de currículo](./lessons/0-course-setup/for-teachers.md) também!
- Como [Executar o código no VSCode ou Codepace](./lessons/0-course-setup/how-to-run.md)
- Criámos uma [lição de configuração](./lessons/0-course-setup/setup.md) para ajudar a configurar o seu ambiente de desenvolvimento. - Para Educadores, também criámos uma [lição de configuração de currículo](./lessons/0-course-setup/for-teachers.md)!
- Como [Executar o código no VSCode ou Codepace](./lessons/0-course-setup/how-to-run.md)
Siga estes passos:
@ -122,7 +121,7 @@ Faça um Fork do Repositório: Clique no botão "Fork" no canto superior direito
Clone o Repositório: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Não se esqueça de dar uma estrela (🌟) a este repositório para encontrá-lo mais facilmente mais tarde.
Não se esqueça de dar uma estrela (🌟) a este repositório para encontrá-lo mais facilmente depois.
## Conheça outros Estudantes
@ -131,39 +130,39 @@ Junte-se ao nosso [servidor oficial de Discord de IA](https://aka.ms/genai-disco
Se tiver feedback sobre o produto ou dúvidas enquanto desenvolve, visite o nosso [Fórum de Desenvolvedores do Azure AI Foundry](https://aka.ms/foundry/forum)
## Questionários
> **Uma nota sobre os questionários**: Todos os questionários estão contidos na pasta Quiz-app em etc\quiz-app, ou [Online Aqui](https://ff-quizzes.netlify.app/). Eles estão ligados às lições, e a aplicação de questionários pode ser executada localmente ou implantada no Azure; siga as instruções na pasta `quiz-app`. Estão a ser localizados gradualmente.
> **Uma nota sobre os questionários**: Todos os questionários estão contidos na pasta Quiz-app em etc\quiz-app, ou [Online Aqui](https://ff-quizzes.netlify.app/). Eles estão ligados a partir das lições, e a aplicação de questionários pode ser executada localmente ou implantada no Azure; siga as instruções na pasta `quiz-app`. Estão a ser localizados gradualmente.
## Ajuda Necessária
Tem sugestões ou encontrou erros de ortografia ou código? Abra uma issue ou crie um pull request.
## Agradecimentos Especiais
* **✍️ Autor Principal:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Editora:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustradora de Sketchnotes:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Criadora de Questionários:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Contribuidores Principais:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ Autor Principal:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Editora:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Ilustradora de Sketchnotes:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Criadora de Questionários:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Contribuidores Principais:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Outros Currículos
A nossa equipa produz outros currículos! Veja:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---
**Aviso Legal**:
Este documento foi traduzido utilizando o serviço de tradução por IA [Co-op Translator](https://github.com/Azure/co-op-translator). Embora nos esforcemos para garantir a precisão, é importante notar que traduções automáticas podem conter erros ou imprecisões. O documento original na sua língua nativa deve ser considerado a fonte autoritária. Para informações críticas, recomenda-se a tradução profissional realizada por humanos. Não nos responsabilizamos por quaisquer mal-entendidos ou interpretações incorretas decorrentes da utilização desta tradução.
Este documento foi traduzido utilizando o serviço de tradução por IA [Co-op Translator](https://github.com/Azure/co-op-translator). Embora nos esforcemos para garantir a precisão, é importante ter em conta que traduções automáticas podem conter erros ou imprecisões. O documento original na sua língua nativa deve ser considerado a fonte autoritária. Para informações críticas, recomenda-se a tradução profissional realizada por humanos. Não nos responsabilizamos por quaisquer mal-entendidos ou interpretações incorretas decorrentes da utilização desta tradução.

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# Inteligență Artificială pentru Începători - Un Curriculum
# Inteligența Artificială pentru Începători - Un Curriculum
|![Sketchnote de @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.ro.png)|
|:---:|
| AI Pentru Începători - _Sketchnote de [@girlie_mac](https://twitter.com/girlie_mac)_ |
| AI pentru Începători - _Sketchnote de [@girlie_mac](https://twitter.com/girlie_mac)_ |
Explorează lumea **Inteligenței Artificiale** (AI) cu curriculum-ul nostru de 12 săptămâni și 24 de lecții! Acesta include lecții practice, teste și laboratoare. Curriculum-ul este prietenos pentru începători și acoperă instrumente precum TensorFlow și PyTorch, precum și etica în AI.
### 🌐 Suport Multi-Limbă
#### Suportat prin GitHub Action (Automatizat & Mereu Actualizat)
#### Suportat prin GitHub Action (Automatizat și Mereu Actualizat)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](./README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Dacă dorești să fie suportate limbi suplimentare, acestea sunt listate [aici](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Dacă doriți să aveți suport pentru limbi suplimentare, acestea sunt listate [aici](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Alătură-te Comunității
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Ce vei învăța
**[Mindmap-ul Cursului](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[Harta mentală a cursului](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
În acest curriculum, vei învăța:
* Diferite abordări ale Inteligenței Artificiale, inclusiv abordarea simbolică "bună și veche" cu **Reprezentarea Cunoștințelor** și raționamentul ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Rețele Neurale** și **Învățare Profundă**, care sunt în centrul AI-ului modern. Vom ilustra conceptele din spatele acestor subiecte importante folosind cod în două dintre cele mai populare framework-uri - [TensorFlow](http://Tensorflow.org) și [PyTorch](http://pytorch.org).
* **Arhitecturi Neurale** pentru lucrul cu imagini și text. Vom acoperi modele recente, dar este posibil să nu includem cele mai avansate.
* Abordări mai puțin populare ale AI, cum ar fi **Algoritmi Genetici** și **Sisteme Multi-Agent**.
* Diferite abordări ale Inteligenței Artificiale, inclusiv abordarea simbolică „veche, dar bună” cu **Reprezentarea Cunoștințelor** și raționamentul ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Rețele Neuronale** și **Învățare Profundă**, care sunt esențiale pentru AI modernă. Vom ilustra conceptele din spatele acestor subiecte importante folosind cod în două dintre cele mai populare cadre - [TensorFlow](http://Tensorflow.org) și [PyTorch](http://pytorch.org).
* **Arhitecturi Neuronale** pentru lucrul cu imagini și text. Vom acoperi modele recente, dar este posibil să nu includem cele mai noi inovații.
* Abordări mai puțin populare ale AI, cum ar fi **Algoritmii Genetici** și **Sisteme Multi-Agent**.
Ce nu vom acoperi în acest curriculum:
> [Găsește toate resursele suplimentare pentru acest curs în colecția noastră Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Găsiți toate resursele suplimentare pentru acest curs în colecția noastră Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Cazuri de utilizare ale **AI în Afaceri**. Ia în considerare parcurgerea [Introducere în AI pentru utilizatorii de afaceri](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) pe Microsoft Learn sau [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), dezvoltat în colaborare cu [INSEAD](https://www.insead.edu/).
* **Învățare Automată Clasică**, care este bine descrisă în [Curriculum-ul nostru de Învățare Automată pentru Începători](http://github.com/Microsoft/ML-for-Beginners).
* Aplicații practice AI construite folosind **[Servicii Cognitive](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Pentru aceasta, recomandăm să începi cu modulele Microsoft Learn pentru [viziune](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [procesarea limbajului natural](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI cu Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** și altele.
* Framework-uri specifice ML **Cloud**, cum ar fi [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) sau [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Ia în considerare utilizarea [Construiește și operează soluții de învățare automată cu Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) și [Construiește și operează soluții de învățare automată cu Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI Conversațională** și **Chat Bots**. Există un [Creează soluții AI conversaționale](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) learning path separat, și poți consulta [acest articol de blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) pentru mai multe detalii.
* **Matematica profundă** din spatele învățării profunde. Pentru aceasta, recomandăm [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) de Ian Goodfellow, Yoshua Bengio și Aaron Courville, care este disponibilă online la [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Cazuri de utilizare a **AI în Afaceri**. Luați în considerare parcurgerea traseului de învățare [Introducere în AI pentru utilizatorii de afaceri](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) pe Microsoft Learn sau [Școala de Afaceri AI](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), dezvoltată în colaborare cu [INSEAD](https://www.insead.edu/).
* **Învățarea Automată Clasică**, care este bine descrisă în [Curriculum-ul nostru pentru Începători în Învățarea Automată](http://github.com/Microsoft/ML-for-Beginners).
* Aplicații practice AI construite folosind **[Servicii Cognitive](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Pentru aceasta, vă recomandăm să începeți cu modulele Microsoft Learn pentru [viziune](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [procesarea limbajului natural](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[AI Generativă cu Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** și altele.
* Cadre specifice ML **în Cloud**, cum ar fi [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) sau [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Luați în considerare utilizarea traseelor de învățare [Construirea și operarea soluțiilor de învățare automată cu Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) și [Construirea și operarea soluțiilor de învățare automată cu Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI Conversațională** și **Chat Bots**. Există un traseu de învățare separat [Crearea soluțiilor AI conversaționale](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), iar pentru mai multe detalii puteți consulta [această postare pe blog](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/).
* **Matematica Avansată** din spatele învățării profunde. Pentru aceasta, vă recomandăm [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) de Ian Goodfellow, Yoshua Bengio și Aaron Courville, disponibilă și online la [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Pentru o introducere ușoară în subiectele _AI în Cloud_, poți lua în considerare parcurgerea [Începe cu inteligența artificială pe Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) Learning Path.
Pentru o introducere ușoară în subiectele _AI în Cloud_, puteți lua în considerare traseul de învățare [Începeți cu inteligența artificială pe Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Conținut
| | Link Lecție | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Setarea Cursului](./lessons/0-course-setup/setup.md) | [Setează Mediul de Dezvoltare](./lessons/0-course-setup/how-to-run.md) | |
| 0 | [Configurarea Cursului](./lessons/0-course-setup/setup.md) | [Configurați Mediul de Dezvoltare](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Introducere în AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Introducere și Istoria AI](./lessons/1-Intro/README.md) | - | - |
| II | **AI Simbolică** |
| 02 | [Reprezentarea Cunoștințelor și Sisteme Expert](./lessons/2-Symbolic/README.md) | [Sisteme Expert](./lessons/2-Symbolic/Animals.ipynb) / [Ontologie](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Grafic Conceptual](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Introducere în Rețele Neurale**](./lessons/3-NeuralNetworks/README.md) |||
| 02 | [Reprezentarea Cunoștințelor și Sistemele Expert](./lessons/2-Symbolic/README.md) | [Sisteme Expert](./lessons/2-Symbolic/Animals.ipynb) / [Ontologie](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Grafic de Concepte](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Introducere în Rețele Neuronale**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Perceptron Multi-Strat și Crearea propriului Framework](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 04 | [Perceptron Multi-Strat și Crearea propriului Cadru](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Introducere în Framework-uri (PyTorch/TensorFlow) și Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laborator](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Viziune Computațională**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Explorează Viziunea Computațională pe Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Introducere în Viziunea Computațională. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Laborator](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
@ -86,33 +86,33 @@ Pentru o introducere ușoară în subiectele _AI în Cloud_, poți lua în consi
| 11 | [Detectarea Obiectelor](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Laborator](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Segmentare Semantică. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Procesarea Limbajului Natural**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Explorează Procesarea Limbajului Natural pe Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Reprezentarea Textului. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embedări Semantice ale Cuvintelor. Word2Vec și GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelarea Limbajului. Antrenarea propriilor embedări](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laborator](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rețele Neuronale Recurente](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Rețele Recurente Generative](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Laborator](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Recunoașterea Entităților Denumite](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laborator](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Modele de Limbaj Mari, Programarea Prompturilor și Sarcini Few-Shot](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Reprezentarea Textului. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embedări Semantice ale Cuvintelor. Word2Vec și GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modelarea Limbajului. Antrenarea propriilor embedări](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laborator](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rețele Neuronale Recurente](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Rețele Recurente Generative](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Laborator](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Recunoașterea Entităților Denumite](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laborator](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Modele de Limbaj Mari, Programarea Prompturilor și Sarcini Few-Shot](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Alte Tehnici AI** || |
| 21 | [Algoritmi Genetici](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Învățare prin Recompensă Profundă](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Laborator](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 22 | [Învățare Reforțată Profundă](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Laborator](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Sisteme Multi-Agent](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Etica AI** | | |
| 24 | [Etica AI și AI Responsabil](./lessons/7-Ethics/README.md) | [Microsoft Learn: Principii AI Responsabil](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| 24 | [Etica AI și AI Responsabilă](./lessons/7-Ethics/README.md) | [Microsoft Learn: Principii AI Responsabilă](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Extra** | | |
| 25 | [Rețele Multi-Modale, CLIP și VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Fiecare lecție conține
* Material de pre-citire
* Material de pre-lectură
* Jupyter Notebooks executabile, care sunt adesea specifice framework-ului (**PyTorch** sau **TensorFlow**). Notebook-ul executabil conține, de asemenea, mult material teoretic, așa că pentru a înțelege subiectul trebuie să parcurgi cel puțin o versiune a notebook-ului (PyTorch sau TensorFlow).
* **Laboratoare** disponibile pentru unele subiecte, care îți oferă oportunitatea de a aplica materialul învățat la o problemă specifică.
* Unele secțiuni conțin linkuri către modulele [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) care acoperă subiecte conexe.
## Începe
- Am creat o [lecție de configurare](./lessons/0-course-setup/setup.md) pentru a te ajuta să îți configurezi mediul de dezvoltare. - Pentru educatori, am creat și o [lecție de configurare a curriculei](./lessons/0-course-setup/for-teachers.md)!
- Am creat o [lecție de configurare](./lessons/0-course-setup/setup.md) pentru a te ajuta să îți configurezi mediul de dezvoltare. - Pentru educatori, am creat o [lecție de configurare a curriculei](./lessons/0-course-setup/for-teachers.md) și pentru voi!
- Cum să [Rulezi codul în VSCode sau Codepace](./lessons/0-course-setup/how-to-run.md)
Urmează acești pași:
@ -125,12 +125,12 @@ Nu uita să dai stea (🌟) acestui repo pentru a-l găsi mai ușor mai târziu.
## Cunoaște alți cursanți
Alătură-te [serverului oficial AI Discord](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) pentru a întâlni și a face networking cu alți cursanți care urmează acest curs și pentru a primi suport.
Alătură-te [serverului oficial AI Discord](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) pentru a cunoaște și a face networking cu alți cursanți care urmează acest curs și pentru a primi suport.
Dacă ai feedback despre produs sau întrebări în timp ce construiești, vizitează [Forum-ul Dezvoltatorilor Azure AI Foundry](https://aka.ms/foundry/forum)
## Quiz-uri
> **O notă despre chestionare**: Toate chestionarele se află în folderul Quiz-app din etc\quiz-app sau [Online Aici](https://ff-quizzes.netlify.app/). Ele sunt legate din cadrul lecțiilor, iar aplicația de chestionare poate fi rulată local sau implementată pe Azure; urmați instrucțiunile din folderul `quiz-app`. Ele sunt localizate treptat.
> **O notă despre chestionare**: Toate chestionarele se află în folderul Quiz-app din etc\quiz-app, sau [Online Aici](https://ff-quizzes.netlify.app/). Ele sunt legate din cadrul lecțiilor, iar aplicația de chestionare poate fi rulată local sau implementată pe Azure; urmați instrucțiunile din folderul `quiz-app`. Ele sunt localizate treptat.
## Ajutor necesar
Ai sugestii sau ai găsit greșeli de ortografie sau cod? Deschide un issue sau creează un pull request.
@ -165,4 +165,4 @@ Echipa noastră produce și alte cursuri! Verifică:
---
**Declinare de responsabilitate**:
Acest document a fost tradus folosind serviciul de traducere AI [Co-op Translator](https://github.com/Azure/co-op-translator). Deși ne străduim să asigurăm acuratețea, vă rugăm să fiți conștienți că traducerile automate pot conține erori sau inexactități. Documentul original în limba sa natală ar trebui considerat sursa autoritară. Pentru informații critice, se recomandă traducerea profesională realizată de un specialist uman. Nu ne asumăm responsabilitatea pentru eventualele neînțelegeri sau interpretări greșite care pot apărea din utilizarea acestei traduceri.
Acest document a fost tradus folosind serviciul de traducere AI [Co-op Translator](https://github.com/Azure/co-op-translator). Deși ne străduim să asigurăm acuratețea, vă rugăm să rețineți că traducerile automate pot conține erori sau inexactități. Documentul original în limba sa natală ar trebui considerat sursa autoritară. Pentru informații critice, se recomandă traducerea profesională realizată de un specialist uman. Nu ne asumăm responsabilitatea pentru eventualele neînțelegeri sau interpretări greșite care pot apărea din utilizarea acestei traduceri.

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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Искусственный интеллект для начинающих — учебный курс
# Искусственный интеллект для начинающих - учебная программа
|![Скетчноут от @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.ru.png)|
|:---:|
| Искусственный интеллект для начинающих — _Скетчноут от [@girlie_mac](https://twitter.com/girlie_mac)_ |
| Искусственный интеллект для начинающих - _Скетчноут от [@girlie_mac](https://twitter.com/girlie_mac)_ |
Изучите мир **искусственного интеллекта** (ИИ) с нашим 12-недельным курсом, состоящим из 24 уроков! Включает практические занятия, тесты и лабораторные работы. Курс подходит для начинающих и охватывает такие инструменты, как TensorFlow и PyTorch, а также вопросы этики в ИИ.
Исследуйте мир **искусственного интеллекта** (ИИ) с нашей 12-недельной учебной программой, состоящей из 24 уроков! Она включает практические занятия, тесты и лабораторные работы. Программа рассчитана на начинающих и охватывает такие инструменты, как TensorFlow и PyTorch, а также вопросы этики в ИИ.
### 🌐 Поддержка нескольких языков
#### Доступно через GitHub Action (автоматически и всегда актуально)
#### Поддерживается через GitHub Action (автоматически и всегда актуально)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](./README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Если вы хотите добавить поддержку других языков, список доступных языков можно найти [здесь](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Если вы хотите добавить поддержку дополнительных языков, список доступных языков можно найти [здесь](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Присоединяйтесь к сообществу
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -44,25 +44,25 @@ CO_OP_TRANSLATOR_METADATA:
**[Ментальная карта курса](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
В этом курсе вы изучите:
В рамках этой учебной программы вы изучите:
* Различные подходы к искусственному интеллекту, включая "старый добрый" символический подход с использованием **представления знаний** и рассуждений ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Нейронные сети** и **глубокое обучение**, которые лежат в основе современного ИИ. Мы объясним концепции этих важных тем с помощью кода на двух самых популярных фреймворках — [TensorFlow](http://Tensorflow.org) и [PyTorch](http://pytorch.org).
* **Нейронные архитектуры** для работы с изображениями и текстом. Мы рассмотрим современные модели, хотя они могут быть не самыми передовыми.
* Менее популярные подходы к ИИ, такие как **генетические алгоритмы** и **многоагентные системы**.
* Различные подходы к искусственному интеллекту, включая "старый добрый" символический подход с **представлением знаний** и рассуждением ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Нейронные сети** и **глубокое обучение**, которые лежат в основе современного ИИ. Мы объясним ключевые концепции этих тем с помощью кода в двух самых популярных фреймворках - [TensorFlow](http://Tensorflow.org) и [PyTorch](http://pytorch.org).
* **Нейронные архитектуры** для работы с изображениями и текстом. Мы рассмотрим современные модели, хотя они могут быть немного устаревшими.
* Менее популярные подходы к ИИ, такие как **генетические алгоритмы** и **мультиагентные системы**.
Что мы не будем рассматривать в этом курсе:
Что мы не будем рассматривать в этой учебной программе:
> [Все дополнительные материалы к этому курсу можно найти в нашей коллекции Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Найдите все дополнительные ресурсы для этого курса в нашей коллекции Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Бизнес-кейсы использования **ИИ в бизнесе**. Рекомендуем пройти учебный путь [Введение в ИИ для бизнес-пользователей](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) на Microsoft Learn или [Школу ИИ для бизнеса](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), разработанную в сотрудничестве с [INSEAD](https://www.insead.edu/).
* **Классическое машинное обучение**, которое подробно описано в нашем курсе [Машинное обучение для начинающих](http://github.com/Microsoft/ML-for-Beginners).
* Бизнес-кейсы использования **ИИ в бизнесе**. Рекомендуем пройти учебный путь [Введение в ИИ для бизнес-пользователей](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) на Microsoft Learn или [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), разработанный в сотрудничестве с [INSEAD](https://www.insead.edu/).
* **Классическое машинное обучение**, которое хорошо описано в нашей учебной программе [Машинное обучение для начинающих](http://github.com/Microsoft/ML-for-Beginners).
* Практические приложения ИИ, созданные с использованием **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Для этого рекомендуем начать с модулей Microsoft Learn для [компьютерного зрения](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [обработки естественного языка](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Генеративного ИИ с Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** и других.
* Конкретные облачные фреймворки для машинного обучения, такие как [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) или [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Рассмотрите учебные пути [Создание и эксплуатация решений машинного обучения с Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) и [Создание и эксплуатация решений машинного обучения с Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Разговорный ИИ** и **чат-боты**. Существует отдельный учебный путь [Создание решений разговорного ИИ](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), а также вы можете ознакомиться с [этой статьей](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) для получения дополнительной информации.
* **Глубокая математика**, лежащая в основе глубокого обучения. Для этого мы рекомендуем книгу [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) Иэна Гудфеллоу, Йошуа Бенджио и Аарона Курвиля, которая также доступна онлайн на [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Специфические облачные фреймворки для машинного обучения, такие как [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) или [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Рекомендуем пройти учебные пути [Создание и управление решениями машинного обучения с Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) и [Создание и управление решениями машинного обучения с Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Разговорный ИИ** и **чат-боты**. Существует отдельный учебный путь [Создание решений для разговорного ИИ](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), а также можно ознакомиться с [этой статьей](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) для получения дополнительной информации.
* **Глубокая математика** за глубоким обучением. Для этого рекомендуем книгу [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) Иэна Гудфеллоу, Йошуа Бенджио и Аарона Курвилля, которая также доступна онлайн на [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Для мягкого введения в темы _ИИ в облаке_ вы можете пройти учебный путь [Начало работы с искусственным интеллектом на Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
Для мягкого введения в темы _ИИ в облаке_ можно пройти учебный путь [Начало работы с искусственным интеллектом на Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Содержание
@ -76,44 +76,44 @@ CO_OP_TRANSLATOR_METADATA:
| III | [**Введение в нейронные сети**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Перцептрон](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Ноутбук](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Лабораторная работа](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Многослойный перцептрон и создание собственного фреймворка](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Ноутбук](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Лабораторная работа](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Введение в фреймворки (PyTorch/TensorFlow) и переобучение](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лабораторная работа](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| 05 | [Введение в фреймворки (PyTorch/TensorFlow) и переобучение](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Практическое задание](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Компьютерное зрение**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Изучите компьютерное зрение на Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Введение в компьютерное зрение. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Ноутбук](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Лабораторная работа](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Сверточные нейронные сети](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Архитектуры CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Лабораторная работа](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Предобученные сети и перенос обучения](./lessons/4-ComputerVision/08-TransferLearning/README.md) и [Трюки обучения](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лабораторная работа](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Автокодировщики и вариационные автокодировщики (VAE)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 06 | [Введение в компьютерное зрение. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Ноутбук](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Практическое задание](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Сверточные нейронные сети](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Архитектуры CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Практическое задание](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Предобученные сети и трансферное обучение](./lessons/4-ComputerVision/08-TransferLearning/README.md) и [Трюки обучения](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Практическое задание](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Автоэнкодеры и вариационные автоэнкодеры (VAE)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Генеративно-состязательные сети и перенос художественного стиля](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Обнаружение объектов](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Лабораторная работа](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 11 | [Обнаружение объектов](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Практическое задание](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Семантическая сегментация. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Обработка естественного языка**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Изучите обработку естественного языка на Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Представление текста. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Семантические векторные представления слов. Word2Vec и GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Моделирование языка. Обучение собственных векторных представлений](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Лабораторная работа](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Рекуррентные нейронные сети](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Генеративные рекуррентные сети](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Лабораторная работа](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Трансформеры. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Распознавание именованных сущностей](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Лабораторная работа](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Крупные языковые модели, программирование подсказок и задачи с малым количеством примеров](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**Обработка естественного языка (NLP)**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Изучите обработку естественного языка на Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Представление текста. BoW/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Семантические векторные представления слов. Word2Vec и GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Моделирование языка. Обучение собственных векторных представлений](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Практическое задание](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Рекуррентные нейронные сети](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Генеративные рекуррентные сети](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Практическое задание](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Трансформеры. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Распознавание именованных сущностей](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Практическое задание](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Крупные языковые модели, программирование подсказок и задачи с малым количеством примеров](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Другие методы ИИ** || |
| 21 | [Генетические алгоритмы](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Ноутбук](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Глубокое обучение с подкреплением](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Лабораторная работа](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Мультиагентные системы](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| 22 | [Глубокое обучение с подкреплением](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Практическое задание](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Многоагентные системы](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Этика ИИ** | | |
| 24 | [Этика ИИ и ответственный ИИ](./lessons/7-Ethics/README.md) | [Microsoft Learn: Принципы ответственного ИИ](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Дополнения** | | |
| IX | **Дополнительно** | | |
| 25 | [Мультимодальные сети, CLIP и VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Ноутбук](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Каждая лекция включает
* Материалы для предварительного изучения
* Исполняемые Jupyter-ноутбуки, которые часто специфичны для фреймворка (**PyTorch** или **TensorFlow**). Исполняемый ноутбук также содержит много теоретического материала, поэтому для понимания темы необходимо изучить хотя бы одну версию ноутбука (либо PyTorch, либо TensorFlow).
* **Лабораторные работы**, доступные для некоторых тем, которые дают возможность применить изученный материал к конкретной задаче.
* Исполняемые Jupyter-ноутбуки, которые часто специфичны для фреймворка (**PyTorch** или **TensorFlow**). Исполняемый ноутбук также содержит много теоретического материала, поэтому для понимания темы необходимо пройти хотя бы одну версию ноутбука (PyTorch или TensorFlow).
* **Практические задания**, доступные для некоторых тем, которые дают возможность применить изученный материал к конкретной задаче.
* Некоторые разделы содержат ссылки на модули [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum), охватывающие связанные темы.
## Начало работы
- Мы создали [урок по настройке](./lessons/0-course-setup/setup.md), чтобы помочь вам настроить вашу среду разработки. - Для преподавателей мы также создали [урок по настройке учебного плана](./lessons/0-course-setup/for-teachers.md)!
- Как [запустить код в VSCode или Codepace](./lessons/0-course-setup/how-to-run.md)
- Мы создали [урок по настройке](./lessons/0-course-setup/setup.md), чтобы помочь вам настроить среду разработки. - Для преподавателей мы также подготовили [урок по настройке учебного плана](./lessons/0-course-setup/for-teachers.md)!
- Как [запустить код в VSCode или CodeSpace](./lessons/0-course-setup/how-to-run.md)
Следуйте этим шагам:
@ -121,13 +121,13 @@ CO_OP_TRANSLATOR_METADATA:
Клонируйте репозиторий: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Не забудьте поставить звезду (🌟) этому репозиторию, чтобы легче было его найти позже.
Не забудьте поставить звезду (🌟) этому репозиторию, чтобы потом было проще его найти.
## Познакомьтесь с другими учащимися
Присоединяйтесь к нашему [официальному серверу AI в Discord](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), чтобы познакомиться и наладить связи с другими учащимися, проходящими этот курс, и получить поддержку.
Присоединяйтесь к нашему [официальному серверу AI в Discord](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), чтобы познакомиться и пообщаться с другими учащимися, проходящими этот курс, и получить поддержку.
Если у вас есть отзывы о продукте или вопросы во время разработки, посетите наш [форум разработчиков Azure AI Foundry](https://aka.ms/foundry/forum).
Если у вас есть отзывы о продукте или вопросы во время работы, посетите наш [форум разработчиков Azure AI Foundry](https://aka.ms/foundry/forum)
## Викторины
> **Примечание о викторинах**: Все викторины находятся в папке Quiz-app в etc\quiz-app, или [Онлайн здесь](https://ff-quizzes.netlify.app/). Они связаны с уроками, и приложение для викторин можно запускать локально или развертывать на Azure; следуйте инструкциям в папке `quiz-app`. Постепенно они переводятся на другие языки.
@ -157,7 +157,7 @@ CO_OP_TRANSLATOR_METADATA:
- [Кибербезопасность для начинающих](https://github.com/microsoft/Security-101)
- [Веб-разработка для начинающих](https://aka.ms/webdev-beginners)
- [IoT для начинающих](https://aka.ms/iot-beginners)
- [Разработка XR для начинающих](https://github.com/microsoft/xr-development-for-beginners)
- [XR-разработка для начинающих](https://github.com/microsoft/xr-development-for-beginners)
- [Мастерство работы с GitHub Copilot для агентного использования](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Мастерство работы с GitHub Copilot для разработчиков C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Выбери свое приключение с Copilot](https://github.com/microsoft/CopilotAdventures)
@ -165,4 +165,4 @@ CO_OP_TRANSLATOR_METADATA:
---
**Отказ от ответственности**:
Этот документ был переведен с помощью сервиса автоматического перевода [Co-op Translator](https://github.com/Azure/co-op-translator). Несмотря на наши усилия обеспечить точность, автоматические переводы могут содержать ошибки или неточности. Оригинальный документ на его исходном языке следует считать авторитетным источником. Для получения критически важной информации рекомендуется использовать профессиональный перевод человеком. Мы не несем ответственности за любые недоразумения или неправильные интерпретации, возникшие в результате использования данного перевода.
Этот документ был переведен с помощью сервиса автоматического перевода [Co-op Translator](https://github.com/Azure/co-op-translator). Хотя мы стремимся к точности, пожалуйста, учитывайте, что автоматические переводы могут содержать ошибки или неточности. Оригинальный документ на его исходном языке следует считать авторитетным источником. Для получения критически важной информации рекомендуется профессиональный перевод человеком. Мы не несем ответственности за любые недоразумения или неправильные интерпретации, возникшие в результате использования данного перевода.

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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Umelá inteligencia pre začiatočníkov - Učebný plán
# Umelá inteligencia pre začiatočníkov - Kurikulum
|![Sketchnote od @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.sk.png)|
|:---:|
| AI pre začiatočníkov - _Sketchnote od [@girlie_mac](https://twitter.com/girlie_mac)_ |
Preskúmajte svet **umelej inteligencie** (AI) s naším 12-týždňovým učebným plánom, ktorý obsahuje 24 lekcií! Zahŕňa praktické lekcie, kvízy a laboratóriá. Učebný plán je vhodný pre začiatočníkov a pokrýva nástroje ako TensorFlow a PyTorch, ako aj etiku v AI.
Preskúmajte svet **umelej inteligencie** (AI) s naším 12-týždňovým kurikulom, ktoré obsahuje 24 lekcií! Zahŕňa praktické lekcie, kvízy a laboratórne cvičenia. Kurikulum je priateľské k začiatočníkom a pokrýva nástroje ako TensorFlow a PyTorch, ako aj etiku v AI.
### 🌐 Podpora viacerých jazykov
#### Podporované prostredníctvom GitHub Action (automatizované a vždy aktuálne)
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## Čo sa naučíte
**[Myšlienková mapa kurzu](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
V tomto učebnom pláne sa naučíte:
V tomto kurikule sa naučíte:
* Rôzne prístupy k umelej inteligencii, vrátane „starého dobrého“ symbolického prístupu s **reprezentáciou znalostí** a odvodzovaním ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* Rôzne prístupy k umelej inteligencii, vrátane "starého dobrého" symbolického prístupu s **reprezentáciou znalostí** a odôvodňovaním ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neurónové siete** a **hlboké učenie**, ktoré sú jadrom modernej AI. Koncepty za týmito dôležitými témami si ukážeme pomocou kódu v dvoch najpopulárnejších frameworkoch - [TensorFlow](http://Tensorflow.org) a [PyTorch](http://pytorch.org).
* **Neurónové architektúry** na prácu s obrázkami a textom. Pokryjeme aktuálne modely, ale môžeme byť trochu pozadu za najmodernejšími trendmi.
* Menej populárne prístupy AI, ako sú **genetické algoritmy** a **systémy s viacerými agentmi**.
* **Neurónové architektúry** na prácu s obrazmi a textom. Pokryjeme nedávne modely, ale môžeme byť trochu pozadu v porovnaní s najnovšími technológiami.
* Menej populárne prístupy AI, ako sú **genetické algoritmy** a **systémy viacerých agentov**.
Čo tento učebný plán nepokrýva:
Čo v tomto kurikule nepokryjeme:
> [Všetky doplnkové zdroje pre tento kurz nájdete v našej kolekcii Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Nájdite všetky doplnkové zdroje pre tento kurz v našej kolekcii Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Obchodné prípady použitia **AI v biznise**. Zvážte absolvovanie učebnej cesty [Úvod do AI pre obchodných používateľov](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) na Microsoft Learn alebo [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), vyvinuté v spolupráci s [INSEAD](https://www.insead.edu/).
* **Klasické strojové učenie**, ktoré je dobre popísané v našom [učebnom pláne Strojové učenie pre začiatočníkov](http://github.com/Microsoft/ML-for-Beginners).
* Praktické aplikácie AI postavené pomocou **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Na tento účel odporúčame začať s modulmi Microsoft Learn pre [počítačové videnie](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [spracovanie prirodzeného jazyka](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generatívna AI s Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** a ďalšie.
* Špecifické ML **cloudové frameworky**, ako sú [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) alebo [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Zvážte použitie učebných ciest [Vytváranie a prevádzka riešení strojového učenia s Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) a [Vytváranie a prevádzka riešení strojového učenia s Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Konverzačná AI** a **chatboty**. Existuje samostatná učebná cesta [Vytváranie riešení konverzačnej AI](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) a môžete sa tiež odvolať na [tento blogový príspevok](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) pre viac detailov.
* **Hlboká matematika** za hlbokým učením. Na tento účel odporúčame knihu [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) od Iana Goodfellowa, Yoshua Bengia a Aarona Courvilla, ktorá je dostupná aj online na [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Obchodné prípady použitia **AI v biznise**. Zvážte absolvovanie vzdelávacieho kurzu [Úvod do AI pre obchodných používateľov](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) na Microsoft Learn alebo [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), vyvinutého v spolupráci s [INSEAD](https://www.insead.edu/).
* **Klasické strojové učenie**, ktoré je dobre popísané v našom [kurikule Strojové učenie pre začiatočníkov](http://github.com/Microsoft/ML-for-Beginners).
* Praktické aplikácie AI postavené pomocou **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Na tento účel odporúčame začať s modulmi Microsoft Learn pre [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** a ďalšie.
* Špecifické ML **cloudové frameworky**, ako [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) alebo [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Zvážte použitie vzdelávacích kurzov [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) a [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Konverzačná AI** a **chatboty**. Existuje samostatný vzdelávací kurz [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) a môžete sa tiež odvolať na [tento blogový príspevok](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) pre viac detailov.
* **Hlboká matematika** za hlbokým učením. Na tento účel odporúčame knihu [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) od Iana Goodfellowa, Yoshua Bengia a Aarona Courvillea, ktorá je tiež dostupná online na [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Pre jemný úvod do tém _AI v cloude_ môžete zvážiť absolvovanie učebnej cesty [Začíname s umelou inteligenciou na Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
Pre jemný úvod do tém _AI v cloude_ môžete zvážiť absolvovanie vzdelávacieho kurzu [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Obsah
| | Odkaz na lekciu | PyTorch/Keras/TensorFlow | Laboratórium |
| | Odkaz na lekciu | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Nastavenie kurzu](./lessons/0-course-setup/setup.md) | [Nastavenie vývojového prostredia](./lessons/0-course-setup/how-to-run.md) | |
| 0 | [Nastavenie kurzu](./lessons/0-course-setup/setup.md) | [Nastavte si vývojové prostredie](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Úvod do AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Úvod a história AI](./lessons/1-Intro/README.md) | - | - |
| II | **Symbolická AI** |
| 02 | [Reprezentácia znalostí a expertné systémy](./lessons/2-Symbolic/README.md) | [Expertné systémy](./lessons/2-Symbolic/Animals.ipynb) / [Ontológia](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Konceptuálny graf](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Úvod do neurónových sietí**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Laboratórium](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Viacvrstvový perceptron a vytváranie vlastného frameworku](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Laboratórium](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Úvod do rámcov (PyTorch/TensorFlow) a overfittingu](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Viacvrstvový perceptron a vytvorenie vlastného frameworku](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Úvod do frameworkov (PyTorch/TensorFlow) a overfittingu](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Počítačové videnie**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Preskúmajte počítačové videnie na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Úvod do počítačového videnia. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvolučné neurónové siete](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Architektúry CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Predtrénované siete a transfer learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) a [Tréningové triky](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoenkódery a VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generatívne adversariálne siete a prenos umeleckého štýlu](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 10 | [Generatívne protivnícke siete a prenos umeleckého štýlu](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Detekcia objektov](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantická segmentácia. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Spracovanie prirodzeného jazyka**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Preskúmajte spracovanie prirodzeného jazyka na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Reprezentácia textu. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantické slovné vektory. Word2Vec a GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Jazykové modelovanie. Tréning vlastných vektorov](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurentné neurónové siete](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatívne rekurentné siete](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformery. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Rozpoznávanie pomenovaných entít](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Veľké jazykové modely, programovanie pomocou promptov a úlohy s malým počtom príkladov](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Reprezentácia textu. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantické vektorové reprezentácie. Word2Vec a GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Jazykové modelovanie. Tréning vlastných vektorov](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurentné neurónové siete](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generatívne rekurentné siete](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformery. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Rozpoznávanie pomenovaných entít](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Veľké jazykové modely, programovanie pomocou promptov a úlohy s malým počtom príkladov](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Iné techniky AI** || |
| 21 | [Genetické algoritmy](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Hlboké posilňovacie učenie](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -106,7 +106,7 @@ Pre jemný úvod do tém _AI v cloude_ môžete zvážiť absolvovanie učebnej
## Každá lekcia obsahuje
* Materiály na predčítanie
* Spustiteľné Jupyter Notebooky, ktoré sú často špecifické pre daný rámec (**PyTorch** alebo **TensorFlow**). Spustiteľný notebook obsahuje aj množstvo teoretického materiálu, takže na pochopenie témy je potrebné prejsť aspoň jednu verziu notebooku (buď PyTorch alebo TensorFlow).
* Spustiteľné Jupyter Notebooks, ktoré sú často špecifické pre daný framework (**PyTorch** alebo **TensorFlow**). Spustiteľný notebook obsahuje aj množstvo teoretického materiálu, takže na pochopenie témy je potrebné prejsť aspoň jednu verziu notebooku (buď PyTorch alebo TensorFlow).
* **Lab** dostupné pre niektoré témy, ktoré vám dávajú príležitosť vyskúšať si aplikáciu naučeného materiálu na konkrétny problém.
* Niektoré sekcie obsahujú odkazy na moduly [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum), ktoré pokrývajú súvisiace témy.
@ -121,16 +121,16 @@ Forknite repozitár: Kliknite na tlačidlo "Fork" v pravom hornom rohu tejto str
Klonujte repozitár: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Nezabudnite si označiť (🌟) tento repozitár, aby ste ho neskôr ľahšie našli.
Nezabudnite označiť hviezdičkou (🌟) tento repozitár, aby ste ho neskôr ľahšie našli.
## Spoznajte ďalších študentov
Pridajte sa na náš [oficiálny AI Discord server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), kde sa môžete stretnúť a sieťovať s ďalšími študentmi, ktorí absolvujú tento kurz, a získať podporu.
Pripojte sa k nášmu [oficiálnemu AI Discord serveru](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), aby ste sa mohli stretnúť a sieťovať s ďalšími študentmi, ktorí absolvujú tento kurz, a získali podporu.
Ak máte spätnú väzbu na produkt alebo otázky počas budovania, navštívte náš [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Kvízy
> **Poznámka k kvízom**: Všetky kvízy sa nachádzajú v priečinku Quiz-app v etc\quiz-app, alebo [Online tu](https://ff-quizzes.netlify.app/). Sú prepojené priamo z lekcií. Aplikáciu kvízov je možné spustiť lokálne alebo nasadiť na Azure; postupujte podľa pokynov v priečinku `quiz-app`. Postupne sa lokalizujú.
> **Poznámka o kvízoch**: Všetky kvízy sa nachádzajú v priečinku Quiz-app v etc\quiz-app, alebo [Online tu](https://ff-quizzes.netlify.app/). Sú prepojené priamo z lekcií, pričom aplikáciu na kvízy je možné spustiť lokálne alebo nasadiť na Azure; postupujte podľa pokynov v priečinku `quiz-app`. Postupne sa lokalizujú.
## Hľadáme pomoc
Máte návrhy alebo ste našli pravopisné či programové chyby? Vytvorte issue alebo pull request.
@ -165,4 +165,4 @@ Náš tím vytvára aj ďalšie učebné materiály! Pozrite si:
---
**Upozornenie**:
Tento dokument bol preložený pomocou služby AI prekladu [Co-op Translator](https://github.com/Azure/co-op-translator). Aj keď sa snažíme o presnosť, prosím, berte na vedomie, že automatizované preklady môžu obsahovať chyby alebo nepresnosti. Pôvodný dokument v jeho pôvodnom jazyku by mal byť považovaný za autoritatívny zdroj. Pre kritické informácie sa odporúča profesionálny ľudský preklad. Nie sme zodpovední za akékoľvek nedorozumenia alebo nesprávne interpretácie vyplývajúce z použitia tohto prekladu.
Tento dokument bol preložený pomocou služby na automatický preklad [Co-op Translator](https://github.com/Azure/co-op-translator). Aj keď sa snažíme o presnosť, upozorňujeme, že automatické preklady môžu obsahovať chyby alebo nepresnosti. Pôvodný dokument v jeho pôvodnom jazyku by mal byť považovaný za záväzný zdroj. Pre dôležité informácie odporúčame profesionálny ľudský preklad. Nezodpovedáme za akékoľvek nedorozumenia alebo nesprávne interpretácie vyplývajúce z použitia tohto prekladu.

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@ -1,8 +1,8 @@
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@ -21,7 +21,7 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Umetna inteligenca za začetnike - Kurikulum
# Umetna inteligenca za začetnike - Kurikulum
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.sl.png)|
|:---:|
@ -58,11 +58,11 @@ Kaj ne bomo pokrili v tem kurikulumu:
* Poslovne primere uporabe **AI v poslovanju**. Razmislite o tečaju [Uvod v AI za poslovne uporabnike](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) na Microsoft Learn ali [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), razvit v sodelovanju z [INSEAD](https://www.insead.edu/).
* **Klasično strojno učenje**, ki je dobro opisano v našem [kurikulumu Strojno učenje za začetnike](http://github.com/Microsoft/ML-for-Beginners).
* Praktične aplikacije AI, zgrajene z uporabo **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Za to priporočamo, da začnete z moduli Microsoft Learn za [vizijo](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [obdelavo naravnega jezika](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generativna AI z Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** in druge.
* Specifična ML **oblaka ogrodja**, kot so [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) ali [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Razmislite o uporabi učnih poti [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) in [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Pogovorna AI** in **klepetalni roboti**. Obstaja ločena učna pot [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), prav tako pa si lahko ogledate [ta blog prispevek](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) za več podrobnosti.
* Specifična ML **Cloud Frameworks**, kot so [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) ali [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Razmislite o uporabi učnih poti [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) in [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Pogovorna AI** in **klepetalni roboti**. Obstaja ločena učna pot [Ustvarite pogovorne AI rešitve](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), prav tako pa si lahko ogledate [ta blog prispevek](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) za več podrobnosti.
* **Globoka matematika** za globoko učenje. Za to priporočamo knjigo [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) avtorjev Ian Goodfellow, Yoshua Bengio in Aaron Courville, ki je na voljo tudi na spletu na [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Za uvod v teme _AI v oblaku_ razmislite o učni poti [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
Za uvod v teme _AI v oblaku_ razmislite o učni poti [Začnite z umetno inteligenco na Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Vsebina
@ -76,24 +76,24 @@ Za uvod v teme _AI v oblaku_ razmislite o učni poti [Get started with artificia
| III | [**Uvod v nevronske mreže**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Zvezek](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Laboratorij](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Večplastni perceptron in ustvarjanje lastnega ogrodja](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Zvezek](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Laboratorij](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Uvod v ogrodja (PyTorch/TensorFlow) in overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorij](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| 05 | [Uvod v ogrodja (PyTorch/TensorFlow) in prenaučenje](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorij](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Računalniški vid**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Raziščite računalniški vid na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Uvod v računalniški vid. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Zvezek](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Laboratorij](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvolucijske nevronske mreže](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Arhitekture CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Laboratorij](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Vnaprej naučene mreže in prenos učenja](./lessons/4-ComputerVision/08-TransferLearning/README.md) in [Triki za učenje](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorij](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 08 | [Vnaprej naučene mreže in prenos učenja](./lessons/4-ComputerVision/08-TransferLearning/README.md) in [Triki pri učenju](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Laboratorij](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Avtoenkoderji in VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generativne nasprotujoče mreže in prenos umetniškega sloga](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Prepoznavanje objektov](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Laboratorij](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantična segmentacija. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Obdelava naravnega jezika**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Raziščite obdelavo naravnega jezika na Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Predstavitev besedila. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantične besedne vektorske predstavitve. Word2Vec in GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Jezikovno modeliranje. Učenje lastnih predstavitev](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratorij](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurentne nevronske mreže](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generativne rekurentne mreže](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Laboratorij](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformerji. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Prepoznavanje imenovanih entitet](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratorij](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Veliki jezikovni modeli, programiranje s pozivi in naloge z malo primeri](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Predstavitev besedila. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantične besedne vektorske predstavitve. Word2Vec in GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Modeliranje jezika. Učenje lastnih vektorskih predstavitev](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Laboratorij](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurzivne nevronske mreže](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generativne rekurzivne mreže](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Laboratorij](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformatorji. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Prepoznavanje imenovanih entitet](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Laboratorij](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Veliki jezikovni modeli, programiranje z ukazi in naloge z malo primeri](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Druge tehnike umetne inteligence** || |
| 21 | [Genetski algoritmi](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Zvezek](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Globoko okrepljeno učenje](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Laboratorij](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -101,18 +101,18 @@ Za uvod v teme _AI v oblaku_ razmislite o učni poti [Get started with artificia
| VII | **Etika umetne inteligence** | | |
| 24 | [Etika umetne inteligence in odgovorna umetna inteligenca](./lessons/7-Ethics/README.md) | [Microsoft Learn: Načela odgovorne umetne inteligence](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Dodatki** | | |
| 25 | [Večmodalne mreže, CLIP in VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Zvezek](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 25 | [Mreže z več modalnostmi, CLIP in VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Zvezek](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Vsaka lekcija vsebuje
* Gradivo za predhodno branje
* Izvedljive Jupyter zvezke, ki so pogosto specifični za ogrodje (**PyTorch** ali **TensorFlow**). Izvedljivi zvezek vsebuje tudi veliko teoretičnega gradiva, zato je za razumevanje teme potrebno prebrati vsaj eno različico zvezka (PyTorch ali TensorFlow).
* **Laboratorije**, ki so na voljo za nekatere teme in vam omogočajo, da preizkusite uporabo naučenega gradiva na določenem problemu.
* Izvedljive Jupyter zvezke, ki so pogosto specifični za ogrodje (**PyTorch** ali **TensorFlow**). Izvedljiv zvezek vsebuje tudi veliko teoretičnega gradiva, zato je za razumevanje teme potrebno prebrati vsaj eno različico zvezka (PyTorch ali TensorFlow).
* **Laboratorije**, ki so na voljo za nekatere teme in vam omogočajo, da preizkusite uporabo naučenega gradiva na specifičnem problemu.
* Nekateri razdelki vsebujejo povezave do modulov [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum), ki pokrivajo sorodne teme.
## Začetek
- Pripravili smo [lekcijo za nastavitev](./lessons/0-course-setup/setup.md), ki vam pomaga pri nastavitvi razvojnega okolja. - Za učitelje smo pripravili tudi [lekcijo za nastavitev kurikuluma](./lessons/0-course-setup/for-teachers.md)!
- Ustvarili smo [lekcijo za nastavitev](./lessons/0-course-setup/setup.md), ki vam bo pomagala pri nastavitvi razvojnega okolja. - Za učitelje smo pripravili tudi [lekcijo za nastavitev učnega načrta](./lessons/0-course-setup/for-teachers.md)!
- Kako [zagnati kodo v VSCode ali Codepace](./lessons/0-course-setup/how-to-run.md)
Sledite tem korakom:
@ -131,38 +131,38 @@ Pridružite se našemu [uradnemu AI Discord strežniku](https://aka.ms/genai-dis
## Kvizi
> **Opomba o kvizih**: Vsi kvizi se nahajajo v mapi Quiz-app v etc\quiz-app, ali [na spletu tukaj](https://ff-quizzes.netlify.app/). Povezani so znotraj lekcij, aplikacijo za kvize pa je mogoče zagnati lokalno ali namestiti na Azure; sledite navodilom v mapi `quiz-app`. Postopoma se lokalizirajo.
## Potrebna pomoč
## Potrebujemo pomoč
Imate predloge ali ste našli napake v črkovanju ali kodi? Odprite težavo ali ustvarite zahtevo za združitev.
Imate predloge ali ste našli pravopisne ali programske napake? Odprite težavo ali ustvarite zahtevo za združitev.
## Posebna zahvala
* **✍️ Glavni avtor:** [Dmitry Soshnikov](http://soshnikov.com), doktor znanosti
* **🔥 Urednica:** [Jen Looper](https://twitter.com/jenlooper), doktor znanosti
* **🎨 Ilustratorka skic:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Ustvarjalka kvizov:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Glavni sodelavci:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ Glavni avtor:** [Dmitry Soshnikov](http://soshnikov.com), doktor znanosti
* **🔥 Urednica:** [Jen Looper](https://twitter.com/jenlooper), doktorica znanosti
* **🎨 Ilustratorka skic:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Ustvarjalka kvizov:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Glavni sodelavci:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Drugi učni načrti
Naša ekipa ustvarja tudi druge učne načrte! Oglejte si:
- [Generativna umetna inteligenca za začetnike](https://aka.ms/genai-beginners)
- [Generativna umetna inteligenca za začetnike .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generativna umetna inteligenca z JavaScriptom](https://github.com/microsoft/generative-ai-with-javascript)
- [Generativna umetna inteligenca z Javo](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [Umetna inteligenca za začetnike](https://aka.ms/ai-beginners)
- [Podatkovna znanost za začetnike](https://aka.ms/datascience-beginners)
- [Strojno učenje za začetnike](https://aka.ms/ml-beginners)
- [Kibernetska varnost za začetnike](https://github.com/microsoft/Security-101)
- [Razvoj spletnih aplikacij za začetnike](https://aka.ms/webdev-beginners)
- [IoT za začetnike](https://aka.ms/iot-beginners)
- [Razvoj XR za začetnike](https://github.com/microsoft/xr-development-for-beginners)
- [Obvladovanje GitHub Copilot za agentno uporabo](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Obvladovanje GitHub Copilot za razvijalce C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Izberite svojo Copilot pustolovščino](https://github.com/microsoft/CopilotAdventures)
- [Generativna umetna inteligenca za začetnike](https://aka.ms/genai-beginners)
- [Generativna umetna inteligenca za začetnike .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generativna umetna inteligenca z JavaScriptom](https://github.com/microsoft/generative-ai-with-javascript)
- [Generativna umetna inteligenca z Javo](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [Umetna inteligenca za začetnike](https://aka.ms/ai-beginners)
- [Podatkovna znanost za začetnike](https://aka.ms/datascience-beginners)
- [Strojno učenje za začetnike](https://aka.ms/ml-beginners)
- [Kibernetska varnost za začetnike](https://github.com/microsoft/Security-101)
- [Spletni razvoj za začetnike](https://aka.ms/webdev-beginners)
- [IoT za začetnike](https://aka.ms/iot-beginners)
- [XR razvoj za začetnike](https://github.com/microsoft/xr-development-for-beginners)
- [Obvladovanje GitHub Copilota za agentno uporabo](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Obvladovanje GitHub Copilota za razvijalce C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Izberi svojo Copilot pustolovščino](https://github.com/microsoft/CopilotAdventures)
---
**Omejitev odgovornosti**:
Ta dokument je bil preveden z uporabo storitve za strojno prevajanje [Co-op Translator](https://github.com/Azure/co-op-translator). Čeprav si prizadevamo za natančnost, vas prosimo, da upoštevate, da lahko avtomatizirani prevodi vsebujejo napake ali netočnosti. Izvirni dokument v njegovem izvirnem jeziku je treba obravnavati kot avtoritativni vir. Za ključne informacije priporočamo strokovno človeško prevajanje. Ne prevzemamo odgovornosti za morebitna nesporazuma ali napačne razlage, ki bi nastale zaradi uporabe tega prevoda.
Ta dokument je bil preveden z uporabo storitve za prevajanje z umetno inteligenco [Co-op Translator](https://github.com/Azure/co-op-translator). Čeprav si prizadevamo za natančnost, vas prosimo, da upoštevate, da lahko avtomatizirani prevodi vsebujejo napake ali netočnosti. Izvirni dokument v njegovem maternem jeziku je treba obravnavati kot avtoritativni vir. Za ključne informacije priporočamo profesionalni človeški prevod. Ne prevzemamo odgovornosti za morebitna napačna razumevanja ali napačne interpretacije, ki bi nastale zaradi uporabe tega prevoda.

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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Вештачка интелигенција за почетнике - Наставни план
# Вештачка интелигенција за почетнике - Наставни план
|![Илустрација од @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.sr.png)|
|:---:|
| Вештачка интелигенција за почетнике - _Илустрација од [@girlie_mac](https://twitter.com/girlie_mac)_ |
|![Скетч од @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.sr.png)|
|:---:|
| Вештачка интелигенција за почетнике - _Скетч од [@girlie_mac](https://twitter.com/girlie_mac)_ |
Истражите свет **вештачке интелигенције** (AI) уз наш наставни план од 12 недеља и 24 лекције! Укључује практичне лекције, квизове и лабораторије. Наставни план је прилагођен почетницима и обухвата алате као што су TensorFlow и PyTorch, као и етику у области вештачке интелигенције.
Истражите свет **вештачке интелигенције** (AI) уз наш наставни план од 12 недеља и 24 лекције! Укључује практичне лекције, квизове и лабораторијске вежбе. Наставни план је прилагођен почетницима и покрива алате као што су TensorFlow и PyTorch, као и етику у AI.
### 🌐 Подршка за више језика
### 🌐 Подршка за више језика
#### Подржано преко GitHub Action-а (аутоматски и увек ажурирано)
#### Подржано преко GitHub Action (аутоматски и увек ажурирано)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](./README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](./README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Ако желите да подржимо додатне језике, листа подржаних језика је доступна [овде](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Ако желите да додате још језика, подржани језици су наведени [овде](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Придружите се заједници
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Придружите се заједници
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Шта ћете научити
## Шта ћете научити
**[Мапа курса](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[Мапа курса](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
У овом наставном плану ћете научити:
У овом наставном плану, научићете:
* Различите приступе вештачкој интелигенцији, укључујући „добри стари“ симболички приступ са **репрезентацијом знања** и резоновањем ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Неуронске мреже** и **дубоко учење**, који су у сржи савремене вештачке интелигенције. Концепте иза ових важних тема илустроваћемо кодом у два најпопуларнија оквира - [TensorFlow](http://Tensorflow.org) и [PyTorch](http://pytorch.org).
* **Неуронске архитектуре** за рад са сликама и текстом. Покрићемо новије моделе, али можда ћемо бити мање детаљни у погледу најсавременијих решења.
* Мање популарне приступе вештачкој интелигенцији, као што су **генетски алгоритми** и **системи са више агената**.
* Различите приступе вештачкој интелигенцији, укључујући "добри стари" симболички приступ са **репрезентацијом знања** и резоновањем ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Неуронске мреже** и **дубоко учење**, који су у срцу модерне вештачке интелигенције. Илустроваћемо концепте иза ових важних тема користећи код у два најпопуларнија оквира - [TensorFlow](http://Tensorflow.org) и [PyTorch](http://pytorch.org).
* **Неуронске архитектуре** за рад са сликама и текстом. Покрићемо новије моделе, али можда нећемо обухватити најсавременије.
* Мање популарне AI приступе, као што су **генетски алгоритми** и **системи са више агената**.
Шта нећемо покрити у овом наставном плану:
Шта нећемо покрити у овом наставном плану:
> [Пронађите све додатне ресурсе за овај курс у нашој Microsoft Learn колекцији](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [Пронађите све додатне ресурсе за овај курс у нашој Microsoft Learn колекцији](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Пословне случајеве коришћења **вештачке интелигенције у пословању**. Размотрите курс [Увод у вештачку интелигенцију за пословне кориснике](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) на Microsoft Learn платформи или [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), развијен у сарадњи са [INSEAD](https://www.insead.edu/).
* **Класично машинско учење**, које је добро описано у нашем [Наставном плану за машинско учење за почетнике](http://github.com/Microsoft/ML-for-Beginners).
* Практичне примене вештачке интелигенције изграђене коришћењем **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. За ово препоручујемо да почнете са модулима Microsoft Learn за [визуелизацију](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [обраду природног језика](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Генеративну вештачку интелигенцију са Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** и друге.
* Специфичне ML **Cloud Frameworks**, као што су [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), или [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Размотрите коришћење [Изградња и управљање решењима машинског учења са Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) и [Изградња и управљање решењима машинског учења са Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Конверзацијска вештачка интелигенција** и **чет-ботови**. Постоји посебан [Креирање решења за конверзацијску вештачку интелигенцију](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) курс, а можете се обратити и [овом блогу](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) за више детаља.
* **Дубока математика** иза дубоког учења. За ово бисмо препоручили књигу [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) аутора Ian Goodfellow, Yoshua Bengio и Aaron Courville, која је такође доступна онлајн на [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Пословне случајеве коришћења **AI у пословању**. Размотрите курс [Увод у AI за пословне кориснике](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) на Microsoft Learn, или [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), развијен у сарадњи са [INSEAD](https://www.insead.edu/).
* **Класично машинско учење**, које је добро описано у нашем наставном плану [Машинско учење за почетнике](http://github.com/Microsoft/ML-for-Beginners).
* Практичне AI апликације изграђене коришћењем **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. За ово препоручујемо да започнете са модулима Microsoft Learn за [визуализацију](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [обраду природног језика](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Генеративна AI са Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** и друге.
* Специфичне ML **Cloud Frameworks**, као што су [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), или [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Размотрите коришћење [Изградња и управљање решењима машинског учења са Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) и [Изградња и управљање решењима машинског учења са Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) наставних планова.
* **Конверзацијска AI** и **Chat Bots**. Постоји посебан наставни план [Креирање конверзацијских AI решења](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), а можете се обратити и [овом блогу](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) за више детаља.
* **Дубока математика** иза дубоког учења. За ово препоручујемо [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) од Ian Goodfellow, Yoshua Bengio и Aaron Courville, која је такође доступна онлајн на [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
За лаган увод у теме _вештачке интелигенције у облаку_, можете размотрити курс [Почетак рада са вештачком интелигенцијом на Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
За лаган увод у теме _AI у облаку_, можете размотрити курс [Започните са вештачком интелигенцијом на Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) наставни план.
# Садржај
# Садржај
| | Линк ка лекцији | PyTorch/Keras/TensorFlow | Лабораторија |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Подешавање курса](./lessons/0-course-setup/setup.md) | [Подешавање развојног окружења](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Увод у вештачку интелигенцију**](./lessons/1-Intro/README.md) | | |
| 01 | [Увод и историја вештачке интелигенције](./lessons/1-Intro/README.md) | - | - |
| II | **Симболичка вештачка интелигенција** |
| 02 | [Репрезентација знања и експертски системи](./lessons/2-Symbolic/README.md) | [Експертски системи](./lessons/2-Symbolic/Animals.ipynb) / [Онтологија](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Граф концепата](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Увод у неуронске мреже**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Перцептрон](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Бележница](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Лабораторија](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Вишеслојни перцептрон и креирање сопственог оквира](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Бележница](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Лабораторија](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| | Линк лекције | PyTorch/Keras/TensorFlow | Лабораторија |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Подешавање курса](./lessons/0-course-setup/setup.md) | [Подешавање развојног окружења](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Увод у AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Увод и историја AI](./lessons/1-Intro/README.md) | - | - |
| II | **Симболички AI** |
| 02 | [Репрезентација знања и експертски системи](./lessons/2-Symbolic/README.md) | [Експертски системи](./lessons/2-Symbolic/Animals.ipynb) / [Онтологија](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Граф концепата](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Увод у неуронске мреже**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Перцептрон](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Бележница](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Лабораторија](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Вишеслојни перцептрон и креирање сопственог оквира](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Бележница](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Лабораторија](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Увод у оквире (PyTorch/TensorFlow) и пренапрегнутост](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лабораторија](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Рачунарски вид**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Истражите рачунарски вид на Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Увод у рачунарски вид. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Бележница](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Лабораторија](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Конволуционе неуронске мреже](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Архитектуре CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Лабораторија](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Унапред обучене мреже и трансфер учење](./lessons/4-ComputerVision/08-TransferLearning/README.md) и [Трикови за обуку](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лабораторија](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 08 | [Унапред обучене мреже и трансфер учења](./lessons/4-ComputerVision/08-TransferLearning/README.md) и [Трикови за тренирање](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лабораторија](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Аутоенкодери и варијациони аутоенкодери (VAEs)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Генеративне супарничке мреже и пренос уметничког стила](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Детекција објеката](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Лабораторија](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Семантичка сегментација. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Обрада природног језика**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Истражите обраду природног језика на Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Репрезентација текста. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Семантички уграђени вектори речи. Word2Vec и GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Моделирање језика. Обука сопствених уграђених вектора](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Лабораторија](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Рекурентне неуронске мреже](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Генеративне рекурентне мреже](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Лабораторија](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Трансформери. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Препознавање именованих ентитета](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Лабораторија](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Велики језички модели, програмирање упита и задаци са мало примера](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Представљање текста. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Семантички уграђени текст. Word2Vec и GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Моделирање језика. Тренирање сопствених уграђених текстова](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Лабораторија](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Рекурентне неуронске мреже](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Генеративне рекурентне мреже](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Лабораторија](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Трансформери. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Препознавање именованих ентитета](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Лабораторија](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Велики језички модели, програмирање упита и задаци са мало примера](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Остале технике вештачке интелигенције** || |
| 21 | [Генетски алгоритми](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Бележница](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Дубоко појачано учење](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Лабораторија](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Системи са више агената](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Етика вештачке интелигенције** | | |
| 24 | [Етика вештачке интелигенције и одговорна вештачка интелигенција](./lessons/7-Ethics/README.md) | [Microsoft Learn: Принципи одговорне вештачке интелигенције](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Додаци** | | |
| IX | **Додатно** | | |
| 25 | [Мултимодалне мреже, CLIP и VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Бележница](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Свака лекција садржи
* Материјал за претходно читање
* Извршиве Jupyter бележнице, које су често специфичне за оквир (**PyTorch** или **TensorFlow**). Извршива бележница такође садржи доста теоријског материјала, тако да је за разумевање теме потребно проћи барем једну верзију бележнице (или PyTorch или TensorFlow).
* Материјал за предчитање
* Извршиве Jupyter бележнице, које су често специфичне за оквир (**PyTorch** или **TensorFlow**). Извршива бележница такође садржи доста теоријског материјала, па је за разумевање теме потребно проћи бар једну верзију бележнице (или PyTorch или TensorFlow).
* **Лабораторије** доступне за неке теме, које вам пружају прилику да примените научени материјал на одређени проблем.
* Неки делови садрже линкове ка [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) модулима који покривају повезане теме.
* Неке секције садрже линкове ка [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) модулима који покривају повезане теме.
## Почетак
- Направили смо [лекцију за подешавање](./lessons/0-course-setup/setup.md) како бисмо вам помогли у подешавању развојног окружења. - За едукаторе, направили смо и [лекцију за подешавање наставног плана](./lessons/0-course-setup/for-teachers.md)!
- Како [покренути код у VSCode или Codepace-у](./lessons/0-course-setup/how-to-run.md)
- Направили смо [лекцију за подешавање](./lessons/0-course-setup/setup.md) која ће вам помоћи да подесите своје развојно окружење. - За едукаторе, направили смо [лекцију за подешавање наставног плана](./lessons/0-course-setup/for-teachers.md) и за вас!
- Како [покренути код у VSCode или Codepace](./lessons/0-course-setup/how-to-run.md)
Пратите ове кораке:
Следите ове кораке:
Форкујте репозиторијум: Кликните на дугме "Fork" у горњем десном углу ове странице.
Fork-ујте репозиторијум: Кликните на дугме "Fork" у горњем десном углу ове странице.
Клонирајте репозиторијум: `git clone https://github.com/microsoft/AI-For-Beginners.git`
@ -125,12 +125,12 @@ CO_OP_TRANSLATOR_METADATA:
## Упознајте друге учеснике
Придружите се нашем [званичном AI Discord серверу](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) како бисте упознали и умрежили се са другим учесницима који похађају овај курс и добили подршку.
Придружите се нашем [званичном AI Discord серверу](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) да упознате и умрежите се са другим учесницима који похађају овај курс и добијете подршку.
Ако имате повратне информације о производу или питања током изградње, посетите наш [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Квизови
> **Напомена о квизовима**: Сви квизови се налазе у фасцикли Quiz-app у etc\quiz-app, или [онлајн овде](https://ff-quizzes.netlify.app/). Повезани су са лекцијама, а апликација за квизове може се покренути локално или поставити на Azure; пратите упутства у фасцикли `quiz-app`. Постепено се локализују.
> **Напомена о квизовима**: Сви квизови се налазе у фасцикли Quiz-app у etc\quiz-app, или [Онлајн овде](https://ff-quizzes.netlify.app/). Они су повезани са лекцијама, а апликација за квизове може се покренути локално или поставити на Azure; пратите упутства у фасцикли `quiz-app`. Постепено се локализују.
## Потребна Помоћ
Имате предлоге или сте пронашли правописне или програмске грешке? Отворите питање или направите pull request.
@ -156,7 +156,7 @@ CO_OP_TRANSLATOR_METADATA:
- [Машинско учење за почетнике](https://aka.ms/ml-beginners)
- [Сајбер безбедност за почетнике](https://github.com/microsoft/Security-101)
- [Веб развој за почетнике](https://aka.ms/webdev-beginners)
- [Интернет ствари (IoT) за почетнике](https://aka.ms/iot-beginners)
- [IoT за почетнике](https://aka.ms/iot-beginners)
- [XR развој за почетнике](https://github.com/microsoft/xr-development-for-beginners)
- [Усавршавање GitHub Copilot-а за агентску употребу](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Усавршавање GitHub Copilot-а за C#/.NET програмере](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
@ -165,4 +165,4 @@ CO_OP_TRANSLATOR_METADATA:
---
**Одрицање од одговорности**:
Овај документ је преведен коришћењем услуге за превођење помоћу вештачке интелигенције [Co-op Translator](https://github.com/Azure/co-op-translator). Иако се трудимо да превод буде тачан, молимо вас да имате у виду да аутоматизовани преводи могу садржати грешке или нетачности. Оригинални документ на његовом изворном језику треба сматрати меродавним извором. За критичне информације препоручује се професионални превод од стране људи. Не преузимамо одговорност за било каква погрешна тумачења или неспоразуме који могу настати услед коришћења овог превода.
Овај документ је преведен коришћењем услуге за превођење помоћу вештачке интелигенције [Co-op Translator](https://github.com/Azure/co-op-translator). Иако се трудимо да обезбедимо тачност, молимо вас да имате у виду да аутоматски преводи могу садржати грешке или нетачности. Оригинални документ на његовом изворном језику треба сматрати меродавним извором. За критичне информације препоручује се професионални превод од стране људи. Не преузимамо одговорност за било каква погрешна тумачења или неспоразуме који могу настати услед коришћења овог превода.

54
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@ -1,8 +1,8 @@
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@ -27,29 +27,29 @@ CO_OP_TRANSLATOR_METADATA:
|:---:|
| AI för Nybörjare - _Sketchnote av [@girlie_mac](https://twitter.com/girlie_mac)_ |
Utforska världen av **Artificiell Intelligens** (AI) med vår 12-veckors kursplan med 24 lektioner! Den innehåller praktiska lektioner, quiz och labbar. Kursplanen är nybörjarvänlig och täcker verktyg som TensorFlow och PyTorch, samt etik inom AI.
Utforska världen av **Artificiell Intelligens** (AI) med vår 12-veckors kursplan med 24 lektioner! Den innehåller praktiska lektioner, quiz och labbar. Kursplanen är anpassad för nybörjare och täcker verktyg som TensorFlow och PyTorch, samt etik inom AI.
### 🌐 Stöd för flera språk
#### Stöds via GitHub Action (Automatiserat & Alltid Uppdaterat)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](./README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
[Franska](../fr/README.md) | [Spanska](../es/README.md) | [Tyska](../de/README.md) | [Ryska](../ru/README.md) | [Arabiska](../ar/README.md) | [Persiska (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Kinesiska (Förenklad)](../zh/README.md) | [Kinesiska (Traditionell, Macau)](../mo/README.md) | [Kinesiska (Traditionell, Hong Kong)](../hk/README.md) | [Kinesiska (Traditionell, Taiwan)](../tw/README.md) | [Japanska](../ja/README.md) | [Koreanska](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portugisiska (Portugal)](../pt/README.md) | [Portugisiska (Brasilien)](../br/README.md) | [Italienska](../it/README.md) | [Polska](../pl/README.md) | [Turkiska](../tr/README.md) | [Grekiska](../el/README.md) | [Thailändska](../th/README.md) | [Svenska](./README.md) | [Danska](../da/README.md) | [Norska](../no/README.md) | [Finska](../fi/README.md) | [Holländska](../nl/README.md) | [Hebreiska](../he/README.md) | [Vietnamesiska](../vi/README.md) | [Indonesiska](../id/README.md) | [Malajiska](../ms/README.md) | [Tagalog (Filippinska)](../tl/README.md) | [Swahili](../sw/README.md) | [Ungerska](../hu/README.md) | [Tjeckiska](../cs/README.md) | [Slovakiska](../sk/README.md) | [Rumänska](../ro/README.md) | [Bulgariska](../bg/README.md) | [Serbiska (Kyrilliska)](../sr/README.md) | [Kroatiska](../hr/README.md) | [Slovenska](../sl/README.md) | [Ukrainska](../uk/README.md) | [Burmesiska (Myanmar)](../my/README.md)
**Om du vill ha ytterligare översättningar, finns stödda språk listade [här](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Om du vill ha ytterligare översättningar finns stödda språk listade [här](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Gå med i Communityn
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Vad du kommer att lära dig
**[Mindmap av kursen](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[Mindmap över kursen](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
I denna kursplan kommer du att lära dig:
* Olika tillvägagångssätt för Artificiell Intelligens, inklusive den "gamla goda" symboliska metoden med **Kunskapsrepresentation** och resonemang ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* Olika tillvägagångssätt för Artificiell Intelligens, inklusive den "klassiska" symboliska metoden med **Kunskapsrepresentation** och resonemang ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neurala Nätverk** och **Djupinlärning**, som är kärnan i modern AI. Vi kommer att illustrera koncepten bakom dessa viktiga ämnen med kod i två av de mest populära ramverken - [TensorFlow](http://Tensorflow.org) och [PyTorch](http://pytorch.org).
* **Neurala Arkitekturer** för att arbeta med bilder och text. Vi kommer att täcka aktuella modeller men kanske sakna de allra senaste.
* Mindre populära AI-metoder, såsom **Genetiska Algoritmer** och **Multi-Agent System**.
* **Neurala Arkitekturer** för att arbeta med bilder och text. Vi kommer att täcka aktuella modeller men kanske inte de allra senaste.
* Mindre vanliga AI-metoder, såsom **Genetiska Algoritmer** och **Multi-Agent System**.
Vad vi inte kommer att täcka i denna kursplan:
@ -60,13 +60,13 @@ Vad vi inte kommer att täcka i denna kursplan:
* Praktiska AI-applikationer byggda med **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. För detta rekommenderar vi att du börjar med moduler på Microsoft Learn för [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [naturlig språkbehandling](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generativ AI med Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** och andra.
* Specifika ML **Molnramverk**, såsom [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), eller [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Överväg att använda [Bygg och driv maskininlärningslösningar med Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) och [Bygg och driv maskininlärningslösningar med Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) lärvägar.
* **Konverserande AI** och **Chat Bots**. Det finns en separat [Skapa konverserande AI-lösningar](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) lärväg, och du kan också hänvisa till [denna bloggpost](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) för mer detaljer.
* **Djup Matematik** bakom djupinlärning. För detta rekommenderar vi [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) av Ian Goodfellow, Yoshua Bengio och Aaron Courville, som också är tillgänglig online på [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* **Djup Matematik** bakom djupinlärning. För detta rekommenderar vi [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) av Ian Goodfellow, Yoshua Bengio och Aaron Courville, som också finns tillgänglig online på [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
För en mjuk introduktion till _AI i Molnet_ ämnen kan du överväga att ta [Kom igång med artificiell intelligens på Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) lärväg.
För en mjuk introduktion till _AI i Molnet_ kan du överväga att ta [Kom igång med artificiell intelligens på Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) lärväg.
# Innehåll
| | Lektionslänk | PyTorch/Keras/TensorFlow | Lab |
| | Länkar till Lektioner | PyTorch/Keras/TensorFlow | Lab |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Kursinställning](./lessons/0-course-setup/setup.md) | [Ställ in din utvecklingsmiljö](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Introduktion till AI**](./lessons/1-Intro/README.md) | | |
@ -82,18 +82,18 @@ För en mjuk introduktion till _AI i Molnet_ ämnen kan du överväga att ta [Ko
| 07 | [Konvolutionella neurala nätverk](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN-arkitekturer](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Förtränade nätverk och transfer learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) och [Träningsknep](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoders och VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generativa adversarial nätverk & konstnärlig stilöverföring](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 10 | [Generativa motståndsnätverk & konstnärlig stilöverföring](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Objektdetektion](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantisk segmentering. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Naturlig språkbehandling**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Utforska naturlig språkbehandling på Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Textrepresentation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantiska ordembeddingar. Word2Vec och GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Språkmodellering. Träna dina egna embeddingar](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurrenta neurala nätverk](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generativa rekurrenta nätverk](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Stora språkmodeller, promptprogrammering och få-skott-uppgifter](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Textrepresentation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantiska ordinbäddningar. Word2Vec och GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Språkmodellering. Träna dina egna inbäddningar](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Rekurrenta neurala nätverk](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generativa rekurrenta nätverk](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Stora språkmodeller, promptprogrammering och få-shot-uppgifter](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Andra AI-tekniker** || |
| 21 | [Genetiska algoritmer](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Djup förstärkningsinlärning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -107,7 +107,7 @@ För en mjuk introduktion till _AI i Molnet_ ämnen kan du överväga att ta [Ko
* Förberedande läsmaterial
* Körbara Jupyter Notebooks, som ofta är specifika för ramverket (**PyTorch** eller **TensorFlow**). Den körbara notebooken innehåller också mycket teoretiskt material, så för att förstå ämnet behöver du gå igenom minst en version av notebooken (antingen PyTorch eller TensorFlow).
* **Labbar** som är tillgängliga för vissa ämnen, vilket ger dig möjlighet att tillämpa det du har lärt dig på ett specifikt problem.
* **Labs** finns tillgängliga för vissa ämnen, vilket ger dig möjlighet att tillämpa det material du har lärt dig på ett specifikt problem.
* Vissa avsnitt innehåller länkar till [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) moduler som täcker relaterade ämnen.
## Kom igång
@ -130,12 +130,12 @@ Gå med i vår [officiella AI Discord-server](https://aka.ms/genai-discord?WT.mc
Om du har produktfeedback eller frågor medan du bygger, besök vårt [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Quiz
> **En anteckning om frågesporter**: Alla frågesporter finns i mappen Quiz-app i etc\quiz-app, eller [Online Här](https://ff-quizzes.netlify.app/). De är länkade från lektionerna och frågesportsappen kan köras lokalt eller distribueras till Azure; följ instruktionerna i mappen `quiz-app`. De lokaliseras successivt.
## Hjälp Efterlyses
> **En anteckning om frågesporter**: Alla frågesporter finns i mappen Quiz-app i etc\quiz-app, eller [Online Här](https://ff-quizzes.netlify.app/). De är länkade från lektionerna och frågesportsappen kan köras lokalt eller distribueras till Azure; följ instruktionerna i mappen `quiz-app`. De lokaliseras gradvis.
## Hjälp Sökes
Har du förslag eller hittat stavfel eller kodfel? Skapa ett ärende eller en pull request.
## Särskilt Tack
## Speciellt Tack
* **✍️ Huvudförfattare:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Redaktör:** [Jen Looper](https://twitter.com/jenlooper), PhD
@ -158,11 +158,11 @@ Vårt team skapar andra läroplaner! Kolla in:
- [Webbutveckling för Nybörjare](https://aka.ms/webdev-beginners)
- [IoT för Nybörjare](https://aka.ms/iot-beginners)
- [XR-utveckling för Nybörjare](https://github.com/microsoft/xr-development-for-beginners)
- [Bemästra GitHub Copilot för Agentisk Användning](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Bemästra GitHub Copilot för Agentisk användning](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Bemästra GitHub Copilot för C#/.NET-utvecklare](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Välj Ditt Eget Copilot-Äventyr](https://github.com/microsoft/CopilotAdventures)
---
**Ansvarsfriskrivning**:
Detta dokument har översatts med hjälp av AI-översättningstjänsten [Co-op Translator](https://github.com/Azure/co-op-translator). Även om vi strävar efter noggrannhet, vänligen notera att automatiska översättningar kan innehålla fel eller felaktigheter. Det ursprungliga dokumentet på sitt originalspråk bör betraktas som den auktoritativa källan. För kritisk information rekommenderas professionell mänsklig översättning. Vi ansvarar inte för eventuella missförstånd eller feltolkningar som uppstår vid användning av denna översättning.
Detta dokument har översatts med hjälp av AI-översättningstjänsten [Co-op Translator](https://github.com/Azure/co-op-translator). Även om vi strävar efter noggrannhet, vänligen notera att automatiska översättningar kan innehålla fel eller felaktigheter. Det ursprungliga dokumentet på dess originalspråk bör betraktas som den auktoritativa källan. För kritisk information rekommenderas professionell mänsklig översättning. Vi ansvarar inte för eventuella missförstånd eller feltolkningar som uppstår vid användning av denna översättning.

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@ -1,8 +1,8 @@
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@ -21,21 +21,21 @@ CO_OP_TRANSLATOR_METADATA:
[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# Akili Bandia kwa Anayeanza - Mtaala
# Akili Bandia kwa Kompyuta - Mtaala
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.sw.png)|
|:---:|
| AI kwa Anayeanza - _Sketchnote na [@girlie_mac](https://twitter.com/girlie_mac)_ |
| AI Kwa Kompyuta - _Sketchnote na [@girlie_mac](https://twitter.com/girlie_mac)_ |
Gundua ulimwengu wa **Akili Bandia** (AI) kupitia mtaala wetu wa wiki 12, masomo 24! Unajumuisha masomo ya vitendo, majaribio, na maabara. Mtaala huu ni rahisi kwa wanaoanza na unashughulikia zana kama TensorFlow na PyTorch, pamoja na maadili katika AI.
Gundua ulimwengu wa **Akili Bandia** (AI) kupitia mtaala wetu wa wiki 12, masomo 24! Unajumuisha masomo ya vitendo, majaribio, na mazoezi. Mtaala huu ni rafiki kwa wanaoanza na unashughulikia zana kama TensorFlow na PyTorch, pamoja na maadili katika AI.
### 🌐 Msaada wa Lugha Nyingi
#### Inapatikana kupitia GitHub Action (Imeboreshwa Kiotomatiki na Inasasishwa Kila Wakati)
#### Inasaidiwa kupitia GitHub Action (Imefanywa Kiotomatiki & Daima Imeboreshwa)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](./README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Ikiwa ungependa lugha za ziada ziongezwe, orodha ya lugha zinazopatikana inapatikana [hapa](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Ikiwa ungependa lugha za ziada ziongezwe, orodha ya lugha zinazosaidiwa inapatikana [hapa](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Jiunge na Jamii
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -46,23 +46,23 @@ Gundua ulimwengu wa **Akili Bandia** (AI) kupitia mtaala wetu wa wiki 12, masomo
Katika mtaala huu, utajifunza:
* Njia tofauti za Akili Bandia, ikijumuisha njia ya zamani ya alama na **Uwakilishi wa Maarifa** na hoja ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Mitandao ya Neural** na **Deep Learning**, ambazo ni msingi wa AI ya kisasa. Tutaonyesha dhana za mada hizi muhimu kwa kutumia msimbo katika mifumo miwili maarufu - [TensorFlow](http://Tensorflow.org) na [PyTorch](http://pytorch.org).
* **Miundo ya Neural** kwa kazi za picha na maandishi. Tutashughulikia mifano ya hivi karibuni lakini huenda tukakosa hali ya kisasa zaidi.
* Njia zisizo maarufu za AI, kama vile **Algorithimu za Kijenetiki** na **Mifumo ya Wakala Wengi**.
* Njia tofauti za Akili Bandia, ikiwa ni pamoja na mbinu ya zamani ya alama na **Uwakilishi wa Maarifa** na uamuzi ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Mitandao ya Neva** na **Kujifunza kwa Kina**, ambavyo ni msingi wa AI ya kisasa. Tutaonyesha dhana za mada hizi muhimu kwa kutumia msimbo katika mifumo miwili maarufu - [TensorFlow](http://Tensorflow.org) na [PyTorch](http://pytorch.org).
* **Miundo ya Neva** kwa kazi za picha na maandishi. Tutashughulikia mifano ya hivi karibuni lakini huenda tukakosa hali ya kisasa zaidi.
* Njia za AI zisizo maarufu, kama vile **Algorithimu za Kijenetiki** na **Mifumo ya Wakala Wengi**.
Kile ambacho hatutashughulikia katika mtaala huu:
Tunachokosa katika mtaala huu:
> [Pata rasilimali zote za ziada za kozi hii katika mkusanyiko wetu wa Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Matumizi ya biashara ya **AI katika Biashara**. Fikiria kuchukua [Utangulizi wa AI kwa watumiaji wa biashara](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) kwenye Microsoft Learn, au [Shule ya Biashara ya AI](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), iliyotengenezwa kwa kushirikiana na [INSEAD](https://www.insead.edu/).
* **Machine Learning ya Kawaida**, ambayo imeelezewa vizuri katika [Mtaala wa Kujifunza Mashine kwa Anayeanza](http://github.com/Microsoft/ML-for-Beginners).
* Matumizi ya AI ya vitendo yaliyojengwa kwa kutumia **[Huduma za Utambuzi](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Kwa hili, tunapendekeza uanze na moduli za Microsoft Learn kwa [maono](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [usindikaji wa lugha asilia](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI na Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** na nyinginezo.
* Mifumo maalum ya ML **Cloud Frameworks**, kama [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), au [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Fikiria kutumia [Jenga na endesha suluhisho za kujifunza mashine na Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) na [Jenga na Endesha Suluhisho za Kujifunza Mashine na Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI ya Mazungumzo** na **Chat Bots**. Kuna njia tofauti ya [Tengeneza suluhisho za AI za mazungumzo](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), na unaweza pia kurejelea [blogu hii](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) kwa maelezo zaidi.
* **Hisabati ya Kina** nyuma ya deep learning. Kwa hili, tunapendekeza [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) na Ian Goodfellow, Yoshua Bengio na Aaron Courville, ambayo pia inapatikana mtandaoni katika [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Matumizi ya biashara ya **AI katika Biashara**. Fikiria kuchukua [Utangulizi wa AI kwa watumiaji wa biashara](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) kwenye Microsoft Learn, au [Shule ya Biashara ya AI](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), iliyotengenezwa kwa ushirikiano na [INSEAD](https://www.insead.edu/).
* **Kujifunza kwa Mashine ya Kawaida**, ambayo imeelezwa vizuri katika [Mtaala wa Kujifunza kwa Mashine kwa Kompyuta](http://github.com/Microsoft/ML-for-Beginners).
* Matumizi ya AI ya vitendo yaliyotengenezwa kwa kutumia **[Huduma za Utambuzi](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Kwa hili, tunapendekeza uanze na moduli za Microsoft Learn kwa [maono](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [usindikaji wa lugha asilia](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[AI ya Kizazi na Huduma ya Azure OpenAI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** na nyinginezo.
* Mfumo maalum wa ML **Cloud Frameworks**, kama [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), au [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Fikiria kutumia [Jenga na endesha suluhisho za kujifunza kwa mashine na Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) na [Jenga na endesha suluhisho za kujifunza kwa mashine na Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) njia za kujifunza.
* **AI ya Mazungumzo** na **Chat Bots**. Kuna njia tofauti ya kujifunza [Unda suluhisho za AI za mazungumzo](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), na unaweza pia kurejelea [chapisho hili la blogu](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) kwa maelezo zaidi.
* **Hisabati ya Kina** nyuma ya kujifunza kwa kina. Kwa hili, tunapendekeza [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) na Ian Goodfellow, Yoshua Bengio na Aaron Courville, ambayo pia inapatikana mtandaoni katika [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Kwa utangulizi wa polepole wa mada za _AI katika Wingu_, unaweza kufikiria kuchukua [Anza na akili bandia kwenye Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) Njia ya Kujifunza.
Kwa utangulizi rahisi wa mada za _AI katika Wingu_, unaweza kufikiria kuchukua [Anza na akili bandia kwenye Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) Njia ya Kujifunza.
# Yaliyomo
@ -72,31 +72,31 @@ Kwa utangulizi wa polepole wa mada za _AI katika Wingu_, unaweza kufikiria kuchu
| I | [**Utangulizi wa AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Utangulizi na Historia ya AI](./lessons/1-Intro/README.md) | - | - |
| II | **AI ya Alama** |
| 02 | [Uwakilishi wa Maarifa na Mifumo ya Wataalamu](./lessons/2-Symbolic/README.md) | [Mifumo ya Wataalamu](./lessons/2-Symbolic/Animals.ipynb) / [Ontolojia](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Mchoro wa Dhana](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Utangulizi wa Mitandao ya Neural**](./lessons/3-NeuralNetworks/README.md) |||
| 02 | [Uwakilishi wa Maarifa na Mifumo ya Wataalamu](./lessons/2-Symbolic/README.md) | [Mifumo ya Wataalamu](./lessons/2-Symbolic/Animals.ipynb) / [Ontolojia](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Grafu ya Dhana](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Utangulizi wa Mitandao ya Neva**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Maabara](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Perceptron wa Tabaka Nyingi na Kutengeneza Mfumo Wetu Wenyewe](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Maabara](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 04 | [Perceptron ya Tabaka Nyingi na Kuunda Mfumo Wetu Wenyewe](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Maabara](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Utangulizi wa Mfumo (PyTorch/TensorFlow) na Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Uchambuzi wa Picha**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Gundua Uchambuzi wa Picha kwenye Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Utangulizi wa Uchambuzi wa Picha. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Mitandao ya Neural ya Convolutional](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Miundo ya CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Mitandao Iliyofunzwa Awali na Kujifunza Kuhamisha](./lessons/4-ComputerVision/08-TransferLearning/README.md) na [Mbinu za Mafunzo](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoders na VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Mitandao ya Kizazi ya Adversarial & Uhamisho wa Mtindo wa Kitaaluma](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 10 | [Mitandao ya Kizazi ya Adversarial & Uhamishaji wa Mtindo wa Kitaaluma](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Utambuzi wa Vitu](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Ugawaji wa Semantic. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Usindikaji wa Lugha Asilia**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Gundua Usindikaji wa Lugha Asilia kwenye Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Uwakilishi wa Maandishi. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Uwakilishi wa Neno la Semantic. Word2Vec na GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Uundaji wa Lugha. Kufundisha Uwakilishi wako mwenyewe](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Mitandao ya Neural ya Kurudia](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Mitandao ya Kizazi ya Kurudia](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Utambuzi wa Vitu vya Majina](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Miundo Mikubwa ya Lugha, Programu ya Maagizo na Kazi za Few-Shot](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Uwakilishi wa Maandishi. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Uwakilishi wa Neno la Semantic. Word2Vec na GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Uundaji wa Lugha. Kufundisha Uwakilishi wako mwenyewe](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Mitandao ya Neural ya Kurudia](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Mitandao ya Kizazi ya Kurudia](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Utambuzi wa Vitu vya Majina](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Miundo Mikubwa ya Lugha, Programu ya Maagizo na Kazi za Few-Shot](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Mbinu Nyingine za AI** || |
| 21 | [Algorithms za Kijenetiki](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Kujifunza Kuimarisha kwa Kina](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 22 | [Kujifunza kwa Kuimarisha Kina](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Mifumo ya Wakala Wengi](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Maadili ya AI** | | |
| 24 | [Maadili ya AI na AI ya Uwajibikaji](./lessons/7-Ethics/README.md) | [Microsoft Learn: Kanuni za AI ya Uwajibikaji](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
@ -106,7 +106,7 @@ Kwa utangulizi wa polepole wa mada za _AI katika Wingu_, unaweza kufikiria kuchu
## Kila somo linajumuisha
* Vifaa vya kusoma kabla
* Notebooks za Jupyter zinazoweza kutekelezwa, ambazo mara nyingi ni maalum kwa mfumo (**PyTorch** au **TensorFlow**). Notebook inayoweza kutekelezwa pia ina maudhui mengi ya kinadharia, kwa hivyo ili kuelewa mada unahitaji kupitia angalau toleo moja la notebook (ama PyTorch au TensorFlow).
* Notebooks za Jupyter zinazoweza kutekelezwa, ambazo mara nyingi ni maalum kwa mfumo (**PyTorch** au **TensorFlow**). Notebook inayoweza kutekelezwa pia ina maudhui mengi ya nadharia, kwa hivyo ili kuelewa mada unahitaji kupitia angalau toleo moja la notebook (ama PyTorch au TensorFlow).
* **Labs** zinapatikana kwa baadhi ya mada, ambazo zinakupa fursa ya kujaribu kutumia maudhui uliyoyajifunza kwenye tatizo maalum.
* Sehemu zingine zina viungo vya moduli za [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) zinazoshughulikia mada zinazohusiana.
@ -125,12 +125,12 @@ Usisahau kuweka nyota (🌟) kwenye hifadhi hii ili kuipata kwa urahisi baadaye.
## Kutana na Wanafunzi Wengine
Jiunge na [seva rasmi ya Discord ya AI](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) ili kukutana na kuungana na wanafunzi wengine wanaochukua kozi hii na kupata msaada.
Jiunge na [seva rasmi ya AI ya Discord](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) ili kukutana na kuungana na wanafunzi wengine wanaochukua kozi hii na kupata msaada.
Ikiwa una maoni ya bidhaa au maswali wakati wa kujenga tembelea [Jukwaa la Wasanidi wa Azure AI Foundry](https://aka.ms/foundry/forum)
Ikiwa una maoni ya bidhaa au maswali wakati wa kujenga tembelea [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Maswali ya Quiz
> **Maelezo kuhusu maswali ya majaribio**: Maswali yote ya majaribio yanapatikana kwenye folda ya Quiz-app ndani ya etc\quiz-app, au [Mtandaoni Hapa](https://ff-quizzes.netlify.app/). Yameunganishwa kutoka ndani ya masomo, na programu ya maswali ya majaribio inaweza kuendeshwa kwa ndani au kupelekwa kwenye Azure; fuata maelekezo yaliyomo kwenye folda ya `quiz-app`. Yanatafsiriwa hatua kwa hatua.
> **Maelezo kuhusu maswali ya majaribio**: Maswali yote ya majaribio yanapatikana kwenye folda ya Quiz-app ndani ya etc\quiz-app, au [Mtandaoni Hapa](https://ff-quizzes.netlify.app/). Yameunganishwa kutoka ndani ya masomo, na programu ya maswali ya majaribio inaweza kuendeshwa kwenye kompyuta yako au kuwekwa kwenye Azure; fuata maelekezo yaliyopo kwenye folda ya `quiz-app`. Yanatafsiriwa hatua kwa hatua.
## Msaada Unahitajika
Je, una mapendekezo au umepata makosa ya tahajia au ya kificho? Fungua suala au unda ombi la kuvuta mabadiliko.
@ -147,22 +147,22 @@ Je, una mapendekezo au umepata makosa ya tahajia au ya kificho? Fungua suala au
Timu yetu inazalisha mitaala mingine! Angalia:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
- [Generative AI kwa Kompyuta](https://aka.ms/genai-beginners)
- [Generative AI kwa Kompyuta .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI na JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI na Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI kwa Kompyuta](https://aka.ms/ai-beginners)
- [Sayansi ya Takwimu kwa Kompyuta](https://aka.ms/datascience-beginners)
- [ML kwa Kompyuta](https://aka.ms/ml-beginners)
- [Usalama wa Mtandao kwa Kompyuta](https://github.com/microsoft/Security-101)
- [Web Dev kwa Kompyuta](https://aka.ms/webdev-beginners)
- [IoT kwa Kompyuta](https://aka.ms/iot-beginners)
- [Maendeleo ya XR kwa Kompyuta](https://github.com/microsoft/xr-development-for-beginners)
- [Kumiliki GitHub Copilot kwa Matumizi ya Wakala](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Kumiliki GitHub Copilot kwa Waendelezaji wa C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Chagua Safari Yako ya Copilot](https://github.com/microsoft/CopilotAdventures)
---
**Kanusho**:
Hati hii imetafsiriwa kwa kutumia huduma ya tafsiri ya AI [Co-op Translator](https://github.com/Azure/co-op-translator). Ingawa tunajitahidi kwa usahihi, tafadhali fahamu kuwa tafsiri za kiotomatiki zinaweza kuwa na makosa au kutokuwa sahihi. Hati ya asili katika lugha yake ya awali inapaswa kuzingatiwa kama chanzo cha mamlaka. Kwa taarifa muhimu, inashauriwa kutumia tafsiri ya kitaalamu ya binadamu. Hatutawajibika kwa maelewano mabaya au tafsiri zisizo sahihi zinazotokana na matumizi ya tafsiri hii.
Hati hii imetafsiriwa kwa kutumia huduma ya tafsiri ya AI [Co-op Translator](https://github.com/Azure/co-op-translator). Ingawa tunajitahidi kuhakikisha usahihi, tafsiri za kiotomatiki zinaweza kuwa na makosa au kutokuwa sahihi. Hati ya asili katika lugha yake ya awali inapaswa kuchukuliwa kama chanzo cha mamlaka. Kwa taarifa muhimu, tafsiri ya kitaalamu ya binadamu inapendekezwa. Hatutawajibika kwa kutoelewana au tafsiri zisizo sahihi zinazotokana na matumizi ya tafsiri hii.

72
translations/th/README.md
View File

@ -1,8 +1,8 @@
<!--
CO_OP_TRANSLATOR_METADATA:
{
"original_hash": "07191303b7ea2aff1d47e2b0fe4bb862",
"translation_date": "2025-08-29T08:35:19+00:00",
"original_hash": "2c8099af824bae942ca6ea7e53284770",
"translation_date": "2025-09-07T13:51:46+00:00",
"source_file": "README.md",
"language_code": "th"
}
@ -35,7 +35,7 @@ CO_OP_TRANSLATOR_METADATA:
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](./README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**หากคุณต้องการให้รองรับภาษาเพิ่มเติม รายการภาษาที่รองรับสามารถดูได้ [ที่นี่](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**หากคุณต้องการให้มีการรองรับภาษาเพิ่มเติม รายการภาษาที่รองรับสามารถดูได้ [ที่นี่](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## เข้าร่วมชุมชน
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -55,12 +55,12 @@ CO_OP_TRANSLATOR_METADATA:
> [ค้นหาทรัพยากรเพิ่มเติมทั้งหมดสำหรับหลักสูตรนี้ในคอลเลกชัน Microsoft Learn ของเรา](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* กรณีศึกษาทางธุรกิจของการใช้ **AI ในธุรกิจ** ลองพิจารณาเรียนรู้เส้นทาง [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) บน Microsoft Learn หรือ [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) ซึ่งพัฒนาร่วมกับ [INSEAD](https://www.insead.edu/)
* **การเรียนรู้ของเครื่องแบบดั้งเดิม** ซึ่งอธิบายไว้อย่างดีใน [หลักสูตร Machine Learning for Beginners](http://github.com/Microsoft/ML-for-Beginners)
* กรณีศึกษาทางธุรกิจของการใช้ **AI ในธุรกิจ** ลองพิจารณาเรียนรู้เส้นทาง [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) บน Microsoft Learn หรือ [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) ที่พัฒนาร่วมกับ [INSEAD](https://www.insead.edu/)
* **การเรียนรู้ของเครื่องแบบดั้งเดิม** ซึ่งมีการอธิบายไว้อย่างดีใน [หลักสูตร Machine Learning for Beginners](http://github.com/Microsoft/ML-for-Beginners)
* การประยุกต์ใช้ AI เชิงปฏิบัติที่สร้างขึ้นโดยใช้ **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** สำหรับเรื่องนี้ เราแนะนำให้เริ่มต้นด้วยโมดูล Microsoft Learn สำหรับ [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** และอื่นๆ
* เฟรมเวิร์กคลาวด์ ML เฉพาะ เช่น [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) หรือ [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum) ลองพิจารณาเรียนรู้เส้นทาง [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) และ [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum)
* **AI เชิงสนทนา** และ **แชทบอท** มีเส้นทางการเรียนรู้แยกต่างหาก [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) และคุณยังสามารถดูรายละเอียดเพิ่มเติมได้ใน [บล็อกโพสต์นี้](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)
* **คณิตศาสตร์เชิงลึก** ที่อยู่เบื้องหลังการเรียนรู้เชิงลึก สำหรับเรื่องนี้ เราขอแนะนำหนังสือ [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) โดย Ian Goodfellow, Yoshua Bengio และ Aaron Courville ซึ่งสามารถหาอ่านได้ทางออนไลน์ที่ [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)
* **AI เชิงสนทนา** และ **แชทบอท** มีเส้นทางการเรียนรู้แยกต่างหาก [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) และคุณยังสามารถดูรายละเอียดเพิ่มเติมได้ใน [โพสต์บล็อกนี้](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)
* **คณิตศาสตร์เชิงลึก** ที่อยู่เบื้องหลังการเรียนรู้เชิงลึก สำหรับเรื่องนี้ เราขอแนะนำหนังสือ [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) โดย Ian Goodfellow, Yoshua Bengio และ Aaron Courville ซึ่งสามารถอ่านออนไลน์ได้ที่ [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)
สำหรับการแนะนำเบื้องต้นเกี่ยวกับหัวข้อ _AI ในคลาวด์_ คุณอาจพิจารณาเรียนรู้เส้นทาง [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum)
@ -77,63 +77,63 @@ CO_OP_TRANSLATOR_METADATA:
| 03 | [เพอร์เซปตรอน](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [สมุดบันทึก](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [ห้องปฏิบัติการ](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [เพอร์เซปตรอนหลายชั้นและการสร้างเฟรมเวิร์กของเราเอง](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [สมุดบันทึก](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [ห้องปฏิบัติการ](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [แนะนำ Frameworks (PyTorch/TensorFlow) และ Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**การประมวลผลภาพ (Computer Vision)**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [สำรวจการประมวลผลภาพบน Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [แนะนำการประมวลผลภาพ. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Convolutional Neural Networks](./lessons/4-ComputerVision/07-ConvNets/README.md) & [สถาปัตยกรรมของ CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [เครือข่ายที่ผ่านการฝึกฝนล่วงหน้าและ Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) และ [เคล็ดลับการฝึกฝน](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| IV | [**Computer Vision**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [สำรวจ Computer Vision บน Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [แนะนำ Computer Vision. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Convolutional Neural Networks](./lessons/4-ComputerVision/07-ConvNets/README.md) & [สถาปัตยกรรม CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [เครือข่ายที่ผ่านการฝึกมาแล้วและ Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) และ [เคล็ดลับการฝึก](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoders และ VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Generative Adversarial Networks และ Artistic Style Transfer](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [การตรวจจับวัตถุ (Object Detection)](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [การแบ่งส่วนเชิงความหมาย (Semantic Segmentation). U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**การประมวลผลภาษาธรรมชาติ (Natural Language Processing)**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [สำรวจการประมวลผลภาษาธรรมชาติบน Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [การแทนข้อความ. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [การฝังความหมายของคำ. Word2Vec และ GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [การสร้างแบบจำลองภาษา. การฝึกฝนการฝังของคุณเอง](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [การจดจำชื่อเอนทิตี (Named Entity Recognition)](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [โมเดลภาษาขนาดใหญ่, การเขียนโปรแกรม Prompt และ Few-Shot Tasks](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 11 | [Object Detection](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantic Segmentation. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [สำรวจ Natural Language Processing บน Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [การแสดงข้อความ. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantic word embeddings. Word2Vec และ GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [การสร้างแบบจำลองภาษา. การฝึก embeddings ของคุณเอง](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Large Language Models, Prompt Programming และ Few-Shot Tasks](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **เทคนิค AI อื่นๆ** || |
| 21 | [อัลกอริทึมเชิงพันธุกรรม (Genetic Algorithms)](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [การเรียนรู้เสริมเชิงลึก (Deep Reinforcement Learning)](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [ระบบหลายตัวแทน (Multi-Agent Systems)](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| 21 | [Genetic Algorithms](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Deep Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Multi-Agent Systems](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **จริยธรรม AI** | | |
| 24 | [จริยธรรม AI และ AI ที่มีความรับผิดชอบ](./lessons/7-Ethics/README.md) | [Microsoft Learn: หลักการ AI ที่มีความรับผิดชอบ](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **เพิ่มเติม** | | |
| 25 | [เครือข่ายหลายรูปแบบ, CLIP และ VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 25 | [เครือข่าย Multi-Modal, CLIP และ VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## แต่ละบทเรียนประกอบด้วย
* เนื้อหาอ่านล่วงหน้า
* Jupyter Notebooks ที่สามารถรันได้ ซึ่งมักจะเฉพาะเจาะจงกับ Framework (**PyTorch** หรือ **TensorFlow**) Notebook ที่สามารถรันได้ยังมีเนื้อหาเชิงทฤษฎีมากมาย ดังนั้นเพื่อให้เข้าใจหัวข้อ คุณจำเป็นต้องศึกษา Notebook อย่างน้อยหนึ่งเวอร์ชัน (ไม่ว่าจะเป็น PyTorch หรือ TensorFlow)
* **Labs** ที่มีให้สำหรับบางหัวข้อ ซึ่งเปิดโอกาสให้คุณลองนำสิ่งที่คุณได้เรียนรู้ไปประยุกต์ใช้กับปัญหาเฉพาะ
* บางส่วนมีลิงก์ไปยัง [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) โมดูลที่ครอบคลุมหัวข้อที่เกี่ยวข้อง
* Jupyter Notebooks ที่สามารถรันได้ ซึ่งมักจะเฉพาะเจาะจงกับ framework (**PyTorch** หรือ **TensorFlow**) Notebook ที่สามารถรันได้ยังมีเนื้อหาทฤษฎีมากมาย ดังนั้นเพื่อให้เข้าใจหัวข้อ คุณจำเป็นต้องผ่าน Notebook อย่างน้อยหนึ่งเวอร์ชัน (ไม่ว่าจะเป็น PyTorch หรือ TensorFlow)
* **Labs** ที่มีให้สำหรับบางหัวข้อ ซึ่งเปิดโอกาสให้คุณลองนำเนื้อหาที่คุณเรียนรู้ไปใช้กับปัญหาเฉพาะ
* บางส่วนมีลิงก์ไปยังโมดูล [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) ที่ครอบคลุมหัวข้อที่เกี่ยวข้อง
## เริ่มต้นใช้งาน
- เราได้สร้าง [บทเรียนการตั้งค่า](./lessons/0-course-setup/setup.md) เพื่อช่วยคุณตั้งค่าสภาพแวดล้อมการพัฒนา - สำหรับผู้สอน เราได้สร้าง [บทเรียนการตั้งค่าหลักสูตร](./lessons/0-course-setup/for-teachers.md) สำหรับคุณด้วย!
- วิธี [รันโค้ดใน VSCode หรือ Codespace](./lessons/0-course-setup/how-to-run.md)
- วิธี [รันโค้ดใน VSCode หรือ Codepace](./lessons/0-course-setup/how-to-run.md)
ทำตามขั้นตอนเหล่านี้:
Fork Repository: คลิกปุ่ม "Fork" ที่มุมขวาบนของหน้านี้
Fork Repository: คลิกที่ปุ่ม "Fork" ที่มุมขวาบนของหน้านี้
Clone Repository: `git clone https://github.com/microsoft/AI-For-Beginners.git`
อย่าลืมกดดาว (🌟) ให้กับ repo นี้เพื่อให้ค้นหาได้ง่ายในภายหลัง
อย่าลืมดาว (🌟) repo นี้เพื่อให้ค้นหาได้ง่ายขึ้นในภายหลัง
## พบปะผู้เรียนคนอื่นๆ
เข้าร่วม [เซิร์ฟเวอร์ Discord AI อย่างเป็นทางการ](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) เพื่อพบปะและสร้างเครือข่ายกับผู้เรียนคนอื่นๆ ที่กำลังเรียนหลักสูตรนี้และรับการสนับสนุน
หากคุณมีข้อเสนอแนะเกี่ยวกับผลิตภัณฑ์หรือคำถามในขณะที่กำลังสร้าง โปรดเยี่ยมชม [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
หากคุณมีข้อเสนอแนะเกี่ยวกับผลิตภัณฑ์หรือคำถามขณะสร้าง โปรดเยี่ยมชม [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## แบบทดสอบ
> **หมายเหตุเกี่ยวกับแบบทดสอบ**: แบบทดสอบทั้งหมดอยู่ในโฟลเดอร์ Quiz-app ที่ etc\quiz-app หรือ [ออนไลน์ที่นี่](https://ff-quizzes.netlify.app/) แบบทดสอบเหล่านี้ถูกเชื่อมโยงจากบทเรียนต่าง ๆ แอปแบบทดสอบสามารถรันได้ในเครื่องหรือเผยแพร่ไปยัง Azure; ให้ทำตามคำแนะนำในโฟลเดอร์ `quiz-app` แบบทดสอบกำลังถูกแปลเป็นภาษาท้องถิ่นทีละขั้นตอน
> **หมายเหตุเกี่ยวกับแบบทดสอบ**: แบบทดสอบทั้งหมดอยู่ในโฟลเดอร์ Quiz-app ที่ etc\quiz-app หรือ [ออนไลน์ที่นี่](https://ff-quizzes.netlify.app/) แบบทดสอบเหล่านี้ถูกเชื่อมโยงจากบทเรียน และแอปแบบทดสอบสามารถรันได้ในเครื่องหรือเผยแพร่ไปยัง Azure; ให้ทำตามคำแนะนำในโฟลเดอร์ `quiz-app` แบบทดสอบกำลังถูกแปลเป็นภาษาท้องถิ่นทีละขั้นตอน
## ต้องการความช่วยเหลือ
คุณมีข้อเสนอแนะหรือพบข้อผิดพลาดในการสะกดคำหรือโค้ดหรือไม่? โปรดแจ้งปัญหาหรือสร้าง pull request
คุณมีข้อเสนอแนะหรือพบข้อผิดพลาดในการสะกดคำหรือโค้ดหรือไม่? ส่ง Issue หรือสร้าง Pull Request ได้เลย
## ขอบคุณเป็นพิเศษ
@ -141,7 +141,7 @@ Clone Repository: `git clone https://github.com/microsoft/AI-For-Beginners.git`
* **🔥 บรรณาธิการ:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 นักวาดภาพประกอบ Sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ ผู้สร้างแบบทดสอบ:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 ผู้ร่วมงานหลัก:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **🙏 ผู้ร่วมพัฒนาหลัก:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## หลักสูตรอื่น ๆ

100
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@ -1,8 +1,8 @@
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@ -27,15 +27,15 @@ CO_OP_TRANSLATOR_METADATA:
|:---:|
| AI Para sa mga Baguhan - _Sketchnote ni [@girlie_mac](https://twitter.com/girlie_mac)_ |
Tuklasin ang mundo ng **Artipisyal na Intelihensiya** (AI) gamit ang aming 12-linggong, 24-aralin na kurikulum! Kasama rito ang mga praktikal na aralin, pagsusulit, at mga laboratoryo. Ang kurikulum na ito ay para sa mga baguhan at sumasaklaw sa mga tool tulad ng TensorFlow at PyTorch, pati na rin ang etika sa AI.
Tuklasin ang mundo ng **Artipisyal na Intelihensiya** (AI) gamit ang aming 12-linggong, 24-araling kurikulum! Kasama rito ang mga praktikal na aralin, pagsusulit, at mga laboratoryo. Ang kurikulum na ito ay madaling maunawaan ng mga baguhan at sumasaklaw sa mga kasangkapan tulad ng TensorFlow at PyTorch, pati na rin ang etika sa AI.
### 🌐 Suporta sa Iba't Ibang Wika
### 🌐 Suporta sa Maraming Wika
#### Sinusuportahan sa pamamagitan ng GitHub Action (Awtomatiko at Laging Napapanahon)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](../vi/README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](./README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Kung nais mong magkaroon ng karagdagang mga pagsasalin, ang mga sinusuportahang wika ay nakalista [dito](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Kung nais mong magkaroon ng karagdagang mga wika para sa pagsasalin, ang mga sinusuportahang wika ay nakalista [dito](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Sumali sa Komunidad
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -46,23 +46,23 @@ Tuklasin ang mundo ng **Artipisyal na Intelihensiya** (AI) gamit ang aming 12-li
Sa kurikulum na ito, matututuhan mo:
* Iba't ibang paraan sa Artipisyal na Intelihensiya, kabilang ang "lumang paraan" na simbolikong diskarte gamit ang **Knowledge Representation** at pangangatwiran ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neural Networks** at **Deep Learning**, na nasa sentro ng modernong AI. Ipapakita namin ang mga konsepto sa likod ng mga mahahalagang paksang ito gamit ang code sa dalawang pinakasikat na framework - [TensorFlow](http://Tensorflow.org) at [PyTorch](http://pytorch.org).
* Iba't ibang pamamaraan sa Artipisyal na Intelihensiya, kabilang ang "lumang pamamaraan" na simbolikong paraan gamit ang **Knowledge Representation** at pangangatwiran ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Neural Networks** at **Deep Learning**, na siyang sentro ng modernong AI. Ipapakita namin ang mga konsepto sa likod ng mga mahahalagang paksang ito gamit ang code sa dalawa sa pinakapopular na mga framework - [TensorFlow](http://Tensorflow.org) at [PyTorch](http://pytorch.org).
* **Neural Architectures** para sa pagproseso ng mga imahe at teksto. Tatalakayin namin ang mga kamakailang modelo ngunit maaaring kulang sa pinakabagong estado ng sining.
* Hindi gaanong kilalang mga diskarte sa AI, tulad ng **Genetic Algorithms** at **Multi-Agent Systems**.
* Mas kakaunting kilalang pamamaraan ng AI, tulad ng **Genetic Algorithms** at **Multi-Agent Systems**.
Ano ang hindi namin tatalakayin sa kurikulum na ito:
> [Hanapin ang lahat ng karagdagang mapagkukunan para sa kursong ito sa aming Microsoft Learn collection](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Mga kaso ng negosyo ng paggamit ng **AI sa Negosyo**. Isaalang-alang ang pagkuha ng [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) learning path sa Microsoft Learn, o [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), na binuo kasama ang [INSEAD](https://www.insead.edu/).
* Mga kaso ng negosyo sa paggamit ng **AI sa Negosyo**. Isaalang-alang ang pagkuha ng [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) learning path sa Microsoft Learn, o [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), na binuo sa pakikipagtulungan sa [INSEAD](https://www.insead.edu/).
* **Classic Machine Learning**, na mahusay na ipinaliwanag sa aming [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners).
* Praktikal na aplikasyon ng AI gamit ang **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Para dito, inirerekomenda naming magsimula sa mga module ng Microsoft Learn para sa [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** at iba pa.
* Mga praktikal na aplikasyon ng AI na binuo gamit ang **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Para dito, inirerekomenda naming magsimula sa mga module ng Microsoft Learn para sa [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** at iba pa.
* Mga partikular na ML **Cloud Frameworks**, tulad ng [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), o [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Isaalang-alang ang paggamit ng [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) at [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) learning paths.
* **Conversational AI** at **Chat Bots**. May hiwalay na [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) learning path, at maaari ka ring sumangguni sa [blog post na ito](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) para sa higit pang detalye.
* **Malalim na Matematika** sa likod ng deep learning. Para dito, inirerekomenda namin ang [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) nina Ian Goodfellow, Yoshua Bengio, at Aaron Courville, na makukuha rin online sa [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* **Conversational AI** at **Chat Bots**. May hiwalay na [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) learning path, at maaari mo ring tingnan ang [blog post na ito](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) para sa higit pang detalye.
* **Malalim na Matematika** sa likod ng deep learning. Para dito, inirerekomenda namin ang [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) nina Ian Goodfellow, Yoshua Bengio at Aaron Courville, na makukuha rin online sa [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Para sa isang magaan na pagpapakilala sa mga paksang _AI in the Cloud_, maaari mong isaalang-alang ang pagkuha ng [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) Learning Path.
Para sa isang magaan na pagpapakilala sa mga paksa ng _AI sa Cloud_, maaari mong isaalang-alang ang pagkuha ng [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) Learning Path.
# Nilalaman
@ -86,54 +86,54 @@ Para sa isang magaan na pagpapakilala sa mga paksang _AI in the Cloud_, maaari m
| 11 | [Object Detection](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Semantic Segmentation. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Natural Language Processing**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Explore Natural Language Processing on Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Text Representation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantic word embeddings. Word2Vec at GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Language Modeling. Pagsasanay ng Sariling Embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Malalaking Language Models, Prompt Programming at Few-Shot Tasks](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Iba Pang Teknik sa AI** || |
| 13 | [Text Representation. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Semantic word embeddings. Word2Vec at GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Language Modeling. Pagsasanay ng sarili mong embeddings](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Recurrent Neural Networks](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Generative Recurrent Networks](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Named Entity Recognition](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Large Language Models, Prompt Programming at Few-Shot Tasks](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Iba pang Teknik sa AI** || |
| 21 | [Genetic Algorithms](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Deep Reinforcement Learning](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Multi-Agent Systems](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI Ethics** | | |
| 24 | [AI Ethics at Responsible AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Responsible AI Principles](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| VII | **Etika sa AI** | | |
| 24 | [Etika sa AI at Responsible AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Responsible AI Principles](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Mga Extra** | | |
| 25 | [Multi-Modal Networks, CLIP at VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Ang Bawat Lesson ay Naglalaman ng
## Bawat Aralin ay Naglalaman ng
* Mga materyal na dapat basahin bago magsimula
* Mga Jupyter Notebook na maaaring i-execute, na madalas na partikular sa framework (**PyTorch** o **TensorFlow**). Ang mga executable notebook ay naglalaman din ng maraming teoryang materyal, kaya upang maunawaan ang paksa, kailangan mong dumaan sa kahit isang bersyon ng notebook (PyTorch o TensorFlow).
* **Mga Lab** na magagamit para sa ilang mga paksa, na nagbibigay ng pagkakataon na subukan ang paggamit ng mga natutunan sa isang partikular na problema.
* Ang ilang mga seksyon ay naglalaman ng mga link sa [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) na mga module na sumasaklaw sa mga kaugnay na paksa.
* Mga executable na Jupyter Notebooks, na kadalasang partikular sa framework (**PyTorch** o **TensorFlow**). Ang executable notebook ay naglalaman din ng maraming teoretikal na materyal, kaya upang maunawaan ang paksa, kailangan mong dumaan sa kahit isang bersyon ng notebook (PyTorch o TensorFlow).
* **Labs** na magagamit para sa ilang mga paksa, na nagbibigay sa iyo ng pagkakataon na subukan ang paglalapat ng materyal na natutunan sa isang partikular na problema.
* Ang ilang mga seksyon ay naglalaman ng mga link sa [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) modules na sumasaklaw sa mga kaugnay na paksa.
## Pagsisimula
- Gumawa kami ng isang [setup lesson](./lessons/0-course-setup/setup.md) upang tulungan ka sa pag-set up ng iyong development environment. - Para sa mga guro, gumawa rin kami ng isang [curricula setup lesson](./lessons/0-course-setup/for-teachers.md)!
- Nilikha namin ang isang [setup lesson](./lessons/0-course-setup/setup.md) upang tulungan ka sa pag-set up ng iyong development environment. - Para sa mga guro, nilikha rin namin ang isang [curricula setup lesson](./lessons/0-course-setup/for-teachers.md) para sa inyo!
- Paano [Patakbuhin ang code sa VSCode o Codepace](./lessons/0-course-setup/how-to-run.md)
Sundin ang mga hakbang na ito:
Fork ang Repository: I-click ang "Fork" na button sa kanang-itaas na bahagi ng pahinang ito.
Fork ang Repository: I-click ang "Fork" button sa kanang-itaas na bahagi ng pahinang ito.
Clone ang Repository: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Huwag kalimutang i-star (🌟) ang repo na ito upang mas madali mo itong mahanap sa hinaharap.
Huwag kalimutang i-star (🌟) ang repo na ito upang mas madali itong mahanap sa hinaharap.
## Kilalanin ang Iba Pang Mga Nag-aaral
## Makipagkilala sa Ibang Mga Nag-aaral
Sumali sa aming [opisyal na AI Discord server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) upang makipagkita at makipag-network sa iba pang mga nag-aaral na kumukuha ng kursong ito at makakuha ng suporta.
Sumali sa aming [opisyal na AI Discord server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) upang makipagkilala at makipag-network sa ibang mga nag-aaral na kumukuha ng kursong ito at makakuha ng suporta.
Kung mayroon kang feedback sa produkto o mga tanong habang gumagawa, bisitahin ang aming [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Mga Quiz
> **Isang paalala tungkol sa mga pagsusulit**: Ang lahat ng pagsusulit ay matatagpuan sa Quiz-app folder sa etc\quiz-app, o [Online Dito](https://ff-quizzes.netlify.app/). Ang mga ito ay naka-link mula sa loob ng mga aralin. Ang quiz app ay maaaring patakbuhin nang lokal o i-deploy sa Azure; sundin ang mga tagubilin sa `quiz-app` folder. Unti-unti itong isinasalin sa iba't ibang wika.
> **Isang paalala tungkol sa mga pagsusulit**: Ang lahat ng pagsusulit ay matatagpuan sa folder na Quiz-app sa etc\quiz-app, o [Online Dito](https://ff-quizzes.netlify.app/). Ang mga ito ay naka-link mula sa loob ng mga aralin. Ang quiz app ay maaaring patakbuhin nang lokal o i-deploy sa Azure; sundin ang mga tagubilin sa folder na `quiz-app`. Unti-unti itong isinasalin sa iba't ibang wika.
## Kailangan ng Tulong
May mga suhestiyon ka ba o nakakita ng mga pagkakamali sa spelling o code? Magbukas ng isyu o gumawa ng pull request.
May mga suhestiyon ka ba o nakakita ng mga pagkakamali sa spelling o code? Magbukas ng isang isyu o gumawa ng pull request.
## Espesyal na Pasasalamat
@ -147,22 +147,22 @@ May mga suhestiyon ka ba o nakakita ng mga pagkakamali sa spelling o code? Magbu
Ang aming team ay gumagawa rin ng iba pang kurikulum! Tingnan ang mga ito:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
- [Generative AI para sa mga Baguhan](https://aka.ms/genai-beginners)
- [Generative AI para sa mga Baguhan .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI gamit ang JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI gamit ang Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI para sa mga Baguhan](https://aka.ms/ai-beginners)
- [Data Science para sa mga Baguhan](https://aka.ms/datascience-beginners)
- [ML para sa mga Baguhan](https://aka.ms/ml-beginners)
- [Cybersecurity para sa mga Baguhan](https://github.com/microsoft/Security-101)
- [Web Dev para sa mga Baguhan](https://aka.ms/webdev-beginners)
- [IoT para sa mga Baguhan](https://aka.ms/iot-beginners)
- [XR Development para sa mga Baguhan](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot para sa Agentic na Paggamit](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot para sa mga C#/.NET Developer](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Piliin ang Iyong Sariling Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---
**Paunawa**:
Ang dokumentong ito ay isinalin gamit ang AI translation service na [Co-op Translator](https://github.com/Azure/co-op-translator). Bagama't sinisikap naming maging tumpak, pakitandaan na ang mga awtomatikong pagsasalin ay maaaring maglaman ng mga pagkakamali o hindi pagkakatugma. Ang orihinal na dokumento sa orihinal nitong wika ang dapat ituring na opisyal na sanggunian. Para sa mahalagang impormasyon, inirerekomenda ang propesyonal na pagsasalin ng tao. Hindi kami mananagot para sa anumang hindi pagkakaunawaan o maling interpretasyon na maaaring magmula sa paggamit ng pagsasaling ito.
Ang dokumentong ito ay isinalin gamit ang AI translation service na [Co-op Translator](https://github.com/Azure/co-op-translator). Bagama't sinisikap naming maging tumpak, pakitandaan na ang mga awtomatikong pagsasalin ay maaaring maglaman ng mga pagkakamali o hindi pagkakatugma. Ang orihinal na dokumento sa kanyang orihinal na wika ang dapat ituring na opisyal na sanggunian. Para sa mahalagang impormasyon, inirerekomenda ang propesyonal na pagsasalin ng tao. Hindi kami mananagot sa anumang hindi pagkakaunawaan o maling interpretasyon na maaaring magmula sa paggamit ng pagsasaling ito.

104
translations/tr/README.md
View File

@ -1,8 +1,8 @@
<!--
CO_OP_TRANSLATOR_METADATA:
{
"original_hash": "07191303b7ea2aff1d47e2b0fe4bb862",
"translation_date": "2025-08-29T08:21:49+00:00",
"original_hash": "2c8099af824bae942ca6ea7e53284770",
"translation_date": "2025-09-07T13:49:16+00:00",
"source_file": "README.md",
"language_code": "tr"
}
@ -25,17 +25,17 @@ CO_OP_TRANSLATOR_METADATA:
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.tr.png)|
|:---:|
| Yeni Başlayanlar için Yapay Zeka - _[@girlie_mac](https://twitter.com/girlie_mac) tarafından hazırlanan Sketchnote_ |
| Yeni Başlayanlar için Yapay Zeka - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ |
**Yapay Zeka** (AI) dünyasını 12 haftalık, 24 derslik müfredatımızla keşfedin! Müfredat, pratik dersler, testler ve laboratuvar çalışmaları içerir. Yeni başlayanlar için uygundur ve TensorFlow, PyTorch gibi araçların yanı sıra yapay zekada etik konularını da kapsar.
**Yapay Zeka** (AI) dünyasını 12 haftalık, 24 derslik müfredatımızla keşfedin! Pratik dersler, sınavlar ve laboratuvar çalışmaları içerir. Müfredat yeni başlayanlar için uygundur ve TensorFlow, PyTorch gibi araçları ve yapay zekada etik konularını kapsar.
### 🌐 Çok Dilli Destek
#### GitHub Action ile Desteklenir (Otomatik ve Her Zaman Güncel)
[Fransızca](../fr/README.md) | [İspanyolca](../es/README.md) | [Almanca](../de/README.md) | [Rusça](../ru/README.md) | [Arapça](../ar/README.md) | [Farsça](../fa/README.md) | [Urduca](../ur/README.md) | [Çince (Basitleştirilmiş)](../zh/README.md) | [Çince (Geleneksel, Makao)](../mo/README.md) | [Çince (Geleneksel, Hong Kong)](../hk/README.md) | [Çince (Geleneksel, Tayvan)](../tw/README.md) | [Japonca](../ja/README.md) | [Korece](../ko/README.md) | [Hintçe](../hi/README.md) | [Bengalce](../bn/README.md) | [Marathi](../mr/README.md) | [Nepalce](../ne/README.md) | [Pencapça (Gurmukhi)](../pa/README.md) | [Portekizce (Portekiz)](../pt/README.md) | [Portekizce (Brezilya)](../br/README.md) | [İtalyanca](../it/README.md) | [Lehçe](../pl/README.md) | [Türkçe](./README.md) | [Yunanca](../el/README.md) | [Tayca](../th/README.md) | [İsveççe](../sv/README.md) | [Danca](../da/README.md) | [Norveççe](../no/README.md) | [Fince](../fi/README.md) | [Felemenkçe](../nl/README.md) | [İbranice](../he/README.md) | [Vietnamca](../vi/README.md) | [Endonezce](../id/README.md) | [Malayca](../ms/README.md) | [Tagalog (Filipince)](../tl/README.md) | [Svahili](../sw/README.md) | [Macarca](../hu/README.md) | [Çekçe](../cs/README.md) | [Slovakça](../sk/README.md) | [Romence](../ro/README.md) | [Bulgarca](../bg/README.md) | [Sırpça (Kiril)](../sr/README.md) | [Hırvatça](../hr/README.md) | [Slovence](../sl/README.md) | [Ukraynaca](../uk/README.md) | [Burmaca (Myanmar)](../my/README.md)
[Fransızca](../fr/README.md) | [İspanyolca](../es/README.md) | [Almanca](../de/README.md) | [Rusça](../ru/README.md) | [Arapça](../ar/README.md) | [Farsça](../fa/README.md) | [Urduca](../ur/README.md) | [Çince (Basitleştirilmiş)](../zh/README.md) | [Çince (Geleneksel, Macau)](../mo/README.md) | [Çince (Geleneksel, Hong Kong)](../hk/README.md) | [Çince (Geleneksel, Tayvan)](../tw/README.md) | [Japonca](../ja/README.md) | [Korece](../ko/README.md) | [Hintçe](../hi/README.md) | [Bengalce](../bn/README.md) | [Marathi](../mr/README.md) | [Nepalce](../ne/README.md) | [Pencapça (Gurmukhi)](../pa/README.md) | [Portekizce (Portekiz)](../pt/README.md) | [Portekizce (Brezilya)](../br/README.md) | [İtalyanca](../it/README.md) | [Lehçe](../pl/README.md) | [Türkçe](./README.md) | [Yunanca](../el/README.md) | [Tayca](../th/README.md) | [İsveççe](../sv/README.md) | [Danca](../da/README.md) | [Norveççe](../no/README.md) | [Fince](../fi/README.md) | [Felemenkçe](../nl/README.md) | [İbranice](../he/README.md) | [Vietnamca](../vi/README.md) | [Endonezce](../id/README.md) | [Malayca](../ms/README.md) | [Tagalog (Filipince)](../tl/README.md) | [Swahili](../sw/README.md) | [Macarca](../hu/README.md) | [Çekçe](../cs/README.md) | [Slovakça](../sk/README.md) | [Romence](../ro/README.md) | [Bulgarca](../bg/README.md) | [Sırpça (Kiril)](../sr/README.md) | [Hırvatça](../hr/README.md) | [Slovence](../sl/README.md) | [Ukraynaca](../uk/README.md) | [Burma (Myanmar)](../my/README.md)
**Ek dil çevirileri talep etmek isterseniz, desteklenen dillerin listesi [burada](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) bulunmaktadır.**
**Ek dil desteği istiyorsanız, desteklenen diller [burada](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) listelenmiştir.**
## Topluluğa Katılın
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -46,23 +46,23 @@ CO_OP_TRANSLATOR_METADATA:
Bu müfredatta şunları öğreneceksiniz:
* **Bilgi Temsili** ve akıl yürütme gibi "eski usul" sembolik yaklaşımlar da dahil olmak üzere Yapay Zeka'ya farklı yaklaşımlar ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* Modern yapay zekanın temelinde yer alan **Sinir Ağları** ve **Derin Öğrenme**. Bu önemli konuların arkasındaki kavramları, en popüler iki çerçeve olan [TensorFlow](http://Tensorflow.org) ve [PyTorch](http://pytorch.org) kullanarak kodla açıklayacağız.
* Görüntüler ve metinlerle çalışmak için **Sinir Mimarileri**. Güncel modelleri ele alacağız ancak en son teknolojilerde biraz eksik kalabiliriz.
* **Genetik Algoritmalar** ve **Çoklu Ajan Sistemleri** gibi daha az popüler yapay zeka yaklaşımları.
* **Bilgi Temsili** ve akıl yürütme ile "eski usul" sembolik yaklaşım dahil olmak üzere Yapay Zeka'ya farklı yaklaşımlar ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* Modern yapay zekanın temelinde yer alan **Sinir Ağları** ve **Derin Öğrenme**. Bu önemli konuların arkasındaki kavramları, en popüler iki çerçevede - [TensorFlow](http://Tensorflow.org) ve [PyTorch](http://pytorch.org) - kod kullanarak açıklayacağız.
* Görüntüler ve metinlerle çalışmak için **Sinir Mimarileri**. Son modelleri ele alacağız ancak en son teknolojilerde biraz eksik olabiliriz.
* **Genetik Algoritmalar** ve **Çoklu Aracı Sistemler** gibi daha az popüler yapay zeka yaklaşımları.
Bu müfredatta ele almayacağımız konular:
> [Bu kurs için tüm ek kaynakları Microsoft Learn koleksiyonumuzda bulabilirsiniz](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **İş Dünyasında Yapay Zeka** kullanımıyla ilgili iş vakaları. Microsoft Learn'deki [İş kullanıcıları için yapay zekaya giriş](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) öğrenme yolunu veya [AI İşletme Okulu](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)'nu incelemeyi düşünebilirsiniz.
* **İş Dünyasında Yapay Zeka** kullanımıyla ilgili iş vakaları. Microsoft Learn'de [İş kullanıcıları için yapay zekaya giriş](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) öğrenme yolunu veya [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)'u, [INSEAD](https://www.insead.edu/) ile iş birliği içinde geliştirilmiş olanı inceleyin.
* **Klasik Makine Öğrenimi**, bu konu [Yeni Başlayanlar için Makine Öğrenimi Müfredatımızda](http://github.com/Microsoft/ML-for-Beginners) iyi bir şekilde açıklanmıştır.
* **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** kullanılarak oluşturulan pratik yapay zeka uygulamaları. Bunun için, Microsoft Learn'deki [görüş](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [doğal dil işleme](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI Servisi ile Üretici Yapay Zeka](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** ve diğer modüllerle başlamanızı öneririz.
* Belirli ML **Bulut Çerçeveleri**, örneğin [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) veya [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). [Azure Machine Learning ile makine öğrenimi çözümleri oluşturun ve yönetin](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) ve [Azure Databricks ile makine öğrenimi çözümleri oluşturun ve yönetin](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) öğrenme yollarını kullanmayı düşünebilirsiniz.
* **Konuşma Tabanlı Yapay Zeka** ve **Sohbet Botları**. Bunun için ayrı bir [Konuşma tabanlı yapay zeka çözümleri oluşturun](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) öğrenme yolu bulunmaktadır ve daha fazla ayrıntı için [bu blog yazısına](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) başvurabilirsiniz.
* Derin öğrenmenin arkasındaki **Derin Matematik**. Bunun için Ian Goodfellow, Yoshua Bengio ve Aaron Courville tarafından yazılan [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) kitabını öneririz, bu kitap çevrimiçi olarak da mevcuttur: [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** kullanılarak oluşturulmuş pratik yapay zeka uygulamaları. Bunun için Microsoft Learn modüllerinden [görüş](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [doğal dil işleme](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI Servisi ile Üretken Yapay Zeka](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** ve diğerlerini incelemenizi öneririz.
* Belirli ML **Bulut Çerçeveleri**, örneğin [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) veya [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). [Azure Machine Learning ile makine öğrenimi çözümleri oluşturma ve işletme](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) ve [Azure Databricks ile makine öğrenimi çözümleri oluşturma ve işletme](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) öğrenme yollarını kullanmayı düşünün.
* **Konuşma Yapay Zekası** ve **Chat Botlar**. Ayrı bir [Konuşma yapay zeka çözümleri oluşturma](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) öğrenme yolu vardır ve daha fazla ayrıntı için [bu blog yazısına](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) başvurabilirsiniz.
* Derin öğrenmenin arkasındaki **Derin Matematik**. Bunun için Ian Goodfellow, Yoshua Bengio ve Aaron Courville tarafından yazılmış [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) kitabını öneririz, ayrıca çevrimiçi olarak [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) adresinde mevcuttur.
Bulut tabanlı yapay zeka konularına yumuşak bir giriş yapmak için [Azure'da yapay zeka ile tanışın](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) öğrenme yolunu inceleyebilirsiniz.
Bulut üzerinde _Yapay Zeka_ konularına nazik bir giriş yapmak için [Azure'da yapay zeka ile tanışın](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) öğrenme yolunu inceleyebilirsiniz.
# İçerik
@ -77,23 +77,23 @@ Bulut tabanlı yapay zeka konularına yumuşak bir giriş yapmak için [Azure'da
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Lab](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Çok Katmanlı Perceptron ve Kendi Çerçevemizi Oluşturma](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Lab](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Frameworklere Giriş (PyTorch/TensorFlow) ve Aşırı Öğrenme](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Bilgisayarla Görü**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure'da Bilgisayarla Görü Keşfet](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Bilgisayarla Görüye Giriş. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| IV | [**Bilgisayarlı Görü**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Microsoft Azure'da Bilgisayarlı Görü Keşfi](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Bilgisayarlı Görüye Giriş. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Konvolüsyonel Sinir Ağları](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN Mimarileri](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Önceden Eğitilmiş Ağlar ve Transfer Öğrenimi](./lessons/4-ComputerVision/08-TransferLearning/README.md) ve [Eğitim İpuçları](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Otoenkoderler ve VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Üretici Çekişmeli Ağlar ve Sanatsal Stil Transferi](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Nesne Tespiti](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Anlamsal Segmentasyon. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Doğal Dil İşleme**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure'da Doğal Dil İşlemeyi Keşfet](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Metin Temsili. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Anlamsal Kelime Gömüleri. Word2Vec ve GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Dil Modellemesi. Kendi gömülerinizi eğitme](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Tekrarlayan Sinir Ağları](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Üretici Tekrarlayan Ağlar](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Adlandırılmış Varlık Tanıma](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Büyük Dil Modelleri, İpucu Programlama ve Az Örnekli Görevler](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**Doğal Dil İşleme**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure'da Doğal Dil İşleme Keşfi](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Metin Temsili. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Anlamsal Kelime Gömüleri. Word2Vec ve GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Dil Modellemesi. Kendi gömülerinizi eğitmek](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Tekrarlayan Sinir Ağları](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Üretici Tekrarlayan Ağlar](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Adlandırılmış Varlık Tanıma](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Büyük Dil Modelleri, İpucu Programlama ve Az-Örnekli Görevler](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Diğer AI Teknikleri** || |
| 21 | [Genetik Algoritmalar](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Derin Pekiştirmeli Öğrenme](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
@ -103,7 +103,7 @@ Bulut tabanlı yapay zeka konularına yumuşak bir giriş yapmak için [Azure'da
| IX | **Ekstralar** | | |
| 25 | [Çok Modlu Ağlar, CLIP ve VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Her ders şunları içerir
## Her ders şunları içerir:
* Ön okuma materyali
* Çalıştırılabilir Jupyter Notebooks, genellikle belirli bir frameworke (**PyTorch** veya **TensorFlow**) özeldir. Çalıştırılabilir notebook aynı zamanda birçok teorik materyal içerir, bu yüzden konuyu anlamak için notebook'un en az bir versiyonunu (PyTorch veya TensorFlow) incelemeniz gerekir.
@ -113,7 +113,7 @@ Bulut tabanlı yapay zeka konularına yumuşak bir giriş yapmak için [Azure'da
## Başlarken
- Geliştirme ortamınızı kurmanıza yardımcı olmak için bir [kurulum dersi](./lessons/0-course-setup/setup.md) oluşturduk. - Eğitmenler için, sizin için bir [müfredat kurulum dersi](./lessons/0-course-setup/for-teachers.md) de oluşturduk!
- [Kodları VSCode veya Codepace'te Çalıştırma](./lessons/0-course-setup/how-to-run.md)
- [Kodları VSCode veya Codepace'te Çalıştırma](./lessons/0-course-setup/how-to-run.md) hakkında bilgi edinin.
Bu adımları izleyin:
@ -130,39 +130,39 @@ Bu kursu alan diğer öğrencilerle tanışmak ve ağ kurmak için [resmi AI Dis
Ürün geri bildiriminiz veya inşa ederken sorularınız varsa [Azure AI Foundry Geliştirici Forumu](https://aka.ms/foundry/forum)'nu ziyaret edin.
## Sınavlar
> **Sınavlar hakkında bir not**: Tüm sınavlar Quiz-app klasöründe, etc\quiz-app içinde yer alır veya [Buradan Çevrimiçi](https://ff-quizzes.netlify.app/) olarak erişilebilir. Derslerin içinde sınavlara bağlantılar verilmiştir. Quiz uygulaması yerel olarak çalıştırılabilir veya Azure'a dağıtılabilir; `quiz-app` klasöründeki talimatları takip edin. Sınavlar kademeli olarak yerelleştirilmektedir.
> **Sınavlar hakkında bir not**: Tüm sınavlar etc\quiz-app içindeki Quiz-app klasöründe bulunur veya [Çevrimiçi Burada](https://ff-quizzes.netlify.app/) erişilebilir. Sınavlar, derslerin içinde bağlantılıdır. Sınav uygulaması yerel olarak çalıştırılabilir veya Azure'a dağıtılabilir; `quiz-app` klasöründeki talimatları takip edin. Sınavlar kademeli olarak yerelleştirilmektedir.
## Yardım Aranıyor
Önerileriniz mi var ya da yazım veya kod hataları mı buldunuz? Bir sorun oluşturun veya bir pull request gönderin.
Önerileriniz var mı veya yazım ya da kod hataları mı buldunuz? Bir sorun oluşturun veya bir pull request gönderin.
## Özel Teşekkürler
* **✍️ Birincil Yazar:** [Dmitry Soshnikov](http://soshnikov.com), Doktora
* **🔥 Editör:** [Jen Looper](https://twitter.com/jenlooper), Doktora
* **🎨 Sketchnote İllüstratörü:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Quiz Oluşturucu:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Çekirdek Katkıda Bulunanlar:** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ Baş Yazar:** [Dmitry Soshnikov](http://soshnikov.com), PhD
* **🔥 Editör:** [Jen Looper](https://twitter.com/jenlooper), PhD
* **🎨 Sketchnote İllüstratörü:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Quiz Oluşturucu:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Temel Katkıda Bulunanlar:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Diğer Müfredatlar
Ekibimiz başka müfredatlar da hazırlıyor! Göz atın:
Ekibimiz başka müfredatlar da üretiyor! Göz atın:
- [Yeni Başlayanlar için Üretici Yapay Zeka](https://aka.ms/genai-beginners)
- [Yeni Başlayanlar için Üretici Yapay Zeka .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [JavaScript ile Üretici Yapay Zeka](https://github.com/microsoft/generative-ai-with-javascript)
- [Java ile Üretici Yapay Zeka](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [Yeni Başlayanlar için Yapay Zeka](https://aka.ms/ai-beginners)
- [Yeni Başlayanlar için Veri Bilimi](https://aka.ms/datascience-beginners)
- [Yeni Başlayanlar için Makine Öğrenimi](https://aka.ms/ml-beginners)
- [Yeni Başlayanlar için Siber Güvenlik](https://github.com/microsoft/Security-101)
- [Yeni Başlayanlar için Web Geliştirme](https://aka.ms/webdev-beginners)
- [Yeni Başlayanlar için IoT](https://aka.ms/iot-beginners)
- [Yeni Başlayanlar için XR Geliştirme](https://github.com/microsoft/xr-development-for-beginners)
- [Agentic Kullanım için GitHub Copilot’ı Ustalaştırma](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [C#/.NET Geliştiricileri için GitHub Copilot’ı Ustalaştırma](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Kendi Copilot Maceranı Seç](https://github.com/microsoft/CopilotAdventures)
- [Yeni Başlayanlar için Üretken Yapay Zeka](https://aka.ms/genai-beginners)
- [Yeni Başlayanlar için Üretken Yapay Zeka .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [JavaScript ile Üretken Yapay Zeka](https://github.com/microsoft/generative-ai-with-javascript)
- [Java ile Üretken Yapay Zeka](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [Yeni Başlayanlar için Yapay Zeka](https://aka.ms/ai-beginners)
- [Yeni Başlayanlar için Veri Bilimi](https://aka.ms/datascience-beginners)
- [Yeni Başlayanlar için Makine Öğrenimi](https://aka.ms/ml-beginners)
- [Yeni Başlayanlar için Siber Güvenlik](https://github.com/microsoft/Security-101)
- [Yeni Başlayanlar için Web Geliştirme](https://aka.ms/webdev-beginners)
- [Yeni Başlayanlar için IoT](https://aka.ms/iot-beginners)
- [Yeni Başlayanlar için XR Geliştirme](https://github.com/microsoft/xr-development-for-beginners)
- [Agentic Kullanım için GitHub Copilot'u Ustalaştırma](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [C#/.NET Geliştiricileri için GitHub Copilot'u Ustalaştırma](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Kendi Copilot Maceranı Seç](https://github.com/microsoft/CopilotAdventures)
---
**Feragatname**:
Bu belge, [Co-op Translator](https://github.com/Azure/co-op-translator) adlı yapay zeka çeviri hizmeti kullanılarak çevrilmiştir. Doğruluk için çaba göstersek de, otomatik çevirilerin hata veya yanlışlıklar içerebileceğini lütfen unutmayın. Orijinal belgenin kendi dilindeki hali, yetkili kaynak olarak kabul edilmelidir. Kritik bilgiler için profesyonel insan çevirisi önerilir. Bu çevirinin kullanımından kaynaklanan yanlış anlama veya yanlış yorumlamalardan sorumlu değiliz.
Bu belge, [Co-op Translator](https://github.com/Azure/co-op-translator) adlı yapay zeka çeviri hizmeti kullanılarak çevrilmiştir. Doğruluk için çaba göstersek de, otomatik çevirilerin hata veya yanlışlıklar içerebileceğini lütfen unutmayın. Belgenin orijinal dili, yetkili kaynak olarak kabul edilmelidir. Kritik bilgiler için profesyonel insan çevirisi önerilir. Bu çevirinin kullanımından kaynaklanan yanlış anlama veya yanlış yorumlamalardan sorumlu değiliz.

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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# 人工智慧入門課程 - 一個完整的課程
# 人工智慧入門課程 - 課程大綱
|![由 @girlie_mac 繪製的速記圖 https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|:---:|
| 人工智慧入門課程 - _速記圖由 [@girlie_mac](https://twitter.com/girlie_mac) 繪製_ |
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.tw.png)|
|:---:|
| 人工智慧入門課程 - _由 [@girlie_mac](https://twitter.com/girlie_mac) 繪製的速寫筆記_ |
透過我們為期 12 週、共 24 節課的課程，探索 **人工智慧** (AI) 的世界！課程包含實用的教學、測驗和實驗室練習。這是一個適合初學者的課程，涵蓋了像 TensorFlow 和 PyTorch 這樣的工具，以及 AI 的倫理議題。
探索 **人工智慧** (AI) 的世界，透過我們為期 12 週、共 24 節課的課程！課程包含實作教學、測驗以及實驗室練習。這是一個適合初學者的課程，涵蓋了 TensorFlow 和 PyTorch 等工具，以及人工智慧的倫理議題。
### 🌐 多語言支援
### 🌐 多語言支援
#### 透過 GitHub Action 支援（自動化且始終保持最新）
#### 透過 GitHub Action 支援 (自動化且保持最新)
[法文](../fr/README.md) | [西班牙文](../es/README.md) | [德文](../de/README.md) | [俄文](../ru/README.md) | [阿拉伯文](../ar/README.md) | [波斯文 (法爾西)](../fa/README.md) | [烏爾都文](../ur/README.md) | [中文 (簡體)](../zh/README.md) | [中文 (繁體，澳門)](../mo/README.md) | [中文 (繁體，香港)](../hk/README.md) | [中文 (繁體，台灣)](./README.md) | [日文](../ja/README.md) | [韓文](../ko/README.md) | [印地文](../hi/README.md) | [孟加拉文](../bn/README.md) | [馬拉地文](../mr/README.md) | [尼泊爾文](../ne/README.md) | [旁遮普文 (古木基文)](../pa/README.md) | [葡萄牙文 (葡萄牙)](../pt/README.md) | [葡萄牙文 (巴西)](../br/README.md) | [義大利文](../it/README.md) | [波蘭文](../pl/README.md) | [土耳其文](../tr/README.md) | [希臘文](../el/README.md) | [泰文](../th/README.md) | [瑞典文](../sv/README.md) | [丹麥文](../da/README.md) | [挪威文](../no/README.md) | [芬蘭文](../fi/README.md) | [荷蘭文](../nl/README.md) | [希伯來文](../he/README.md) | [越南文](../vi/README.md) | [印尼文](../id/README.md) | [馬來文](../ms/README.md) | [他加祿文 (菲律賓)](../tl/README.md) | [斯瓦希里文](../sw/README.md) | [匈牙利文](../hu/README.md) | [捷克文](../cs/README.md) | [斯洛伐克文](../sk/README.md) | [羅馬尼亞文](../ro/README.md) | [保加利亞文](../bg/README.md) | [塞爾維亞文 (西里爾字母)](../sr/README.md) | [克羅埃西亞文](../hr/README.md) | [斯洛維尼亞文](../sl/README.md) | [烏克蘭文](../uk/README.md) | [緬甸文 (緬甸)](../my/README.md)
[法文](../fr/README.md) | [西班牙文](../es/README.md) | [德文](../de/README.md) | [俄文](../ru/README.md) | [阿拉伯文](../ar/README.md) | [波斯文 (法爾西)](../fa/README.md) | [烏爾都文](../ur/README.md) | [中文 (簡體)](../zh/README.md) | [中文 (繁體，澳門)](../mo/README.md) | [中文 (繁體，香港)](../hk/README.md) | [中文 (繁體，台灣)](./README.md) | [日文](../ja/README.md) | [韓文](../ko/README.md) | [印地文](../hi/README.md) | [孟加拉文](../bn/README.md) | [馬拉地文](../mr/README.md) | [尼泊爾文](../ne/README.md) | [旁遮普文 (古木基)](../pa/README.md) | [葡萄牙文 (葡萄牙)](../pt/README.md) | [葡萄牙文 (巴西)](../br/README.md) | [義大利文](../it/README.md) | [波蘭文](../pl/README.md) | [土耳其文](../tr/README.md) | [希臘文](../el/README.md) | [泰文](../th/README.md) | [瑞典文](../sv/README.md) | [丹麥文](../da/README.md) | [挪威文](../no/README.md) | [芬蘭文](../fi/README.md) | [荷蘭文](../nl/README.md) | [希伯來文](../he/README.md) | [越南文](../vi/README.md) | [印尼文](../id/README.md) | [馬來文](../ms/README.md) | [他加祿文 (菲律賓)](../tl/README.md) | [斯瓦希里文](../sw/README.md) | [匈牙利文](../hu/README.md) | [捷克文](../cs/README.md) | [斯洛伐克文](../sk/README.md) | [羅馬尼亞文](../ro/README.md) | [保加利亞文](../bg/README.md) | [塞爾維亞文 (西里爾字母)](../sr/README.md) | [克羅埃西亞文](../hr/README.md) | [斯洛文尼亞文](../sl/README.md) | [烏克蘭文](../uk/README.md) | [緬甸文 (緬甸)](../my/README.md)
**如果您希望支援其他語言，請參考 [這裡](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**如果您希望支援其他語言，請參考 [此處](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) 列出的支援語言**
## 加入社群
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## 加入社群
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## 您將學到什麼
## 您將學到什麼
**[課程心智圖](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[課程心智圖](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
在這個課程中，您將學到：
在這門課程中，您將學到：
* 不同的人工智慧方法，包括「經典的」符號方法，使用 **知識表徵** 和推理（[GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)）。
* **神經網路** 和 **深度學習**，這是現代 AI 的核心。我們將使用兩個最受歡迎的框架 [TensorFlow](http://Tensorflow.org) 和 [PyTorch](http://pytorch.org) 的程式碼來說明這些重要主題的概念。
* 用於處理影像和文字的 **神經架構**。我們將涵蓋一些近期的模型，但可能不包括最前沿的技術。
* 不太常見的 AI 方法，例如 **遺傳演算法** 和 **多代理系統**。
* 人工智慧的不同方法，包括「經典」符號方法，透過 **知識表示** 和推理 ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))。
* **神經網路** 和 **深度學習**，這是現代人工智慧的核心。我們將使用兩個最受歡迎的框架 [TensorFlow](http://Tensorflow.org) 和 [PyTorch](http://pytorch.org) 的程式碼來說明這些重要主題的概念。
* 用於處理影像和文字的 **神經架構**。我們將涵蓋近期的模型，但可能稍微缺乏最前沿的技術。
* 不太流行的人工智慧方法，例如 **遺傳演算法** 和 **多代理系統**。
我們不會在這個課程中涵蓋：
我們不會在這門課程中涵蓋：
> [在 Microsoft Learn 集合中找到本課程的所有額外資源](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [在 Microsoft Learn 的課程資源集合中找到所有額外資源](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **AI 在商業中的應用案例**。建議參加 [商業用戶的 AI 入門](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，或 [AI 商業學院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)，由 [INSEAD](https://www.insead.edu/) 合作開發。
* **經典機器學習**，這在我們的 [機器學習入門課程](http://github.com/Microsoft/ML-for-Beginners) 中有詳細描述。
* 使用 **[認知服務](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** 構建的實際 AI 應用。建議從 Microsoft Learn 的模組開始，例如 [視覺](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然語言處理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[使用 Azure OpenAI 服務的生成式 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 等。
* 特定的 ML **雲框架**，例如 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) 或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。建議參考 [使用 Azure Machine Learning 構建和運營機器學習解決方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 和 [使用 Azure Databricks 構建和運營機器學習解決方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
* **對話式 AI** 和 **聊天機器人**。有一個單獨的 [創建對話式 AI 解決方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，您也可以參考 [這篇部落格文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) 獲取更多細節。
* **深度學習的數學基礎**。建議參考 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 所著的 [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)，該書也可在線上獲取：[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
* **人工智慧在商業中的應用案例**。建議參加 [商業使用者的人工智慧入門](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，或 [人工智慧商業學院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)，由 [INSEAD](https://www.insead.edu/) 合作開發。
* **經典機器學習**，這在我們的 [機器學習入門課程](http://github.com/Microsoft/ML-for-Beginners) 中有詳細描述。
* 使用 **[認知服務](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** 建立的人工智慧應用。建議從 Microsoft Learn 的模組開始，例如 [視覺](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然語言處理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[Azure OpenAI Service 的生成式人工智慧](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 等。
* 特定的機器學習 **雲端框架**，例如 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)、或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。建議參加 [使用 Azure Machine Learning 建立和操作機器學習解決方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 和 [使用 Azure Databricks 建立和操作機器學習解決方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
* **對話式人工智慧** 和 **聊天機器人**。有一個單獨的 [建立對話式人工智慧解決方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) 學習路徑，您也可以參考 [這篇部落格文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) 了解更多細節。
* **深度學習的數學基礎**。建議參考 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 所著的 [深度學習](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)，也可在線上取得 [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
如果您想要輕鬆入門 _雲端 AI_ 主題，可以考慮參加 [在 Azure 上開始人工智慧之旅](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
若想輕鬆入門 _雲端人工智慧_ 主題，建議參加 [在 Azure 上開始人工智慧學習](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 學習路徑。
# 課程內容
# 課程內容
| | 課程連結 | PyTorch/Keras/TensorFlow | 實驗室 |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [課程設置](./lessons/0-course-setup/setup.md) | [設置您的開發環境](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI 簡介**](./lessons/1-Intro/README.md) | | |
| 01 | [AI 的簡介與歷史](./lessons/1-Intro/README.md) | - | - |
| II | **符號 AI** |
| 02 | [知識表徵與專家系統](./lessons/2-Symbolic/README.md) | [專家系統](./lessons/2-Symbolic/Animals.ipynb) / [本體論](./lessons/2-Symbolic/FamilyOntology.ipynb) /[概念圖](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**神經網路簡介**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [感知器](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [筆記本](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [實驗室](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [多層感知器與創建我們自己的框架](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [筆記本](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [實驗室](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [框架介紹（PyTorch/TensorFlow）與過擬合](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [實驗室](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| | 課程連結 | PyTorch/Keras/TensorFlow | 實驗室 |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [課程設定](./lessons/0-course-setup/setup.md) | [設定您的開發環境](./lessons/0-course-setup/how-to-run.md) | |
| I | [**人工智慧簡介**](./lessons/1-Intro/README.md) | | |
| 01 | [人工智慧的簡介與歷史](./lessons/1-Intro/README.md) | - | - |
| II | **符號人工智慧** |
| 02 | [知識表示與專家系統](./lessons/2-Symbolic/README.md) | [專家系統](./lessons/2-Symbolic/Animals.ipynb) / [本體論](./lessons/2-Symbolic/FamilyOntology.ipynb) /[概念圖](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**神經網路簡介**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [感知器](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [筆記本](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [實驗室](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [多層感知器與建立我們自己的框架](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [筆記本](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [實驗室](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [框架介紹 (PyTorch/TensorFlow) 和過度擬合](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [實驗](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**電腦視覺**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [探索 Microsoft Azure 上的電腦視覺](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [電腦視覺入門. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [筆記本](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [實驗室](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [卷積神經網絡](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN 架構](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [實驗室](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [預訓練網絡與遷移學習](./lessons/4-ComputerVision/08-TransferLearning/README.md) 和 [訓練技巧](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [實驗室](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [自編碼器與變分自編碼器 (VAEs)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [生成對抗網絡 (GANs) 與藝術風格遷移](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [物體檢測](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [實驗室](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 06 | [電腦視覺介紹. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [筆記本](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [實驗](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [卷積神經網絡](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN 架構](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [實驗](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [預訓練網絡和遷移學習](./lessons/4-ComputerVision/08-TransferLearning/README.md) 和 [訓練技巧](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [實驗](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [自編碼器和變分自編碼器 (VAEs)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [生成對抗網絡 (GANs) 和藝術風格遷移](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [物件檢測](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [實驗](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [語義分割. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**自然語言處理**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [探索 Microsoft Azure 上的自然語言處理](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [文本表示. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [語義詞嵌入. Word2Vec 和 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [語言建模. 訓練自己的嵌入](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [實驗室](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [循環神經網絡 (RNN)](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成式循環網絡](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [實驗室](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformer. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [命名實體識別 (NER)](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [實驗室](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大型語言模型、提示編程與少樣本任務](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [文本表示. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [語義詞嵌入. Word2Vec 和 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [語言建模. 訓練自己的嵌入](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [實驗](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [循環神經網絡 (RNN)](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成式循環網絡](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [實驗](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformer. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [命名實體識別 (NER)](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [實驗](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大型語言模型, 提示編程和少樣本任務](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **其他 AI 技術** || |
| 21 | [遺傳算法](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [筆記本](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [深度強化學習](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [實驗室](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 22 | [深度強化學習](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [實驗](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [多代理系統](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI 倫理** | | |
| 24 | [AI 倫理與負責任的 AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: 負責任的 AI 原則](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **附加內容** | | |
| 24 | [AI 倫理和負責任的 AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: 負責任的 AI 原則](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **額外內容** | | |
| 25 | [多模態網絡, CLIP 和 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [筆記本](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## 每節課包含
* 預讀材料
* 可執行的 Jupyter 筆記本，通常針對特定框架（**PyTorch** 或 **TensorFlow**）。可執行的筆記本還包含大量理論材料，因此為了理解主題，您需要至少閱讀一個版本的筆記本（PyTorch 或 TensorFlow）。
* **實驗室**（部分主題提供），讓您有機會將所學應用於具體問題。
* 某些部分包含指向 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模組的鏈接，涵蓋相關主題。
* 可執行的 Jupyter 筆記本，通常特定於框架 (**PyTorch** 或 **TensorFlow**)。可執行的筆記本還包含大量理論材料，因此要理解主題，您需要至少完成一個版本的筆記本（PyTorch 或 TensorFlow）。
* **實驗** 可用於某些主題，讓您有機會將所學材料應用於特定問題。
* 部分章節包含指向 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模組的連結，涵蓋相關主題。
## 開始學習
## 開始使用
- 我們已經創建了一個 [設置課程](./lessons/0-course-setup/setup.md) 幫助您設置開發環境。 - 對於教育者，我們還創建了一個 [課程設置指南](./lessons/0-course-setup/for-teachers.md)！
- 我們已創建 [設置課程](./lessons/0-course-setup/setup.md) 幫助您設置開發環境。 - 對於教育工作者，我們也創建了 [課程設置課程](./lessons/0-course-setup/for-teachers.md)！
- 如何 [在 VSCode 或 Codepace 中運行代碼](./lessons/0-course-setup/how-to-run.md)
請按照以下步驟操作：
按照以下步驟：
分叉此倉庫：點擊此頁面右上角的 "Fork" 按鈕。
Fork 此倉庫：點擊此頁面右上角的 "Fork" 按鈕。
克隆倉庫：`git clone https://github.com/microsoft/AI-For-Beginners.git`
別忘了給這個倉庫加星標 (🌟)，以便以後更容易找到。
別忘了給此倉庫加星 (🌟)，以便以後更容易找到。
## 與其他學習者交流
@ -130,10 +130,10 @@ CO_OP_TRANSLATOR_METADATA:
如果您在構建過程中有產品反饋或問題，請訪問我們的 [Azure AI Foundry 開發者論壇](https://aka.ms/foundry/forum)
## 測驗
> **關於測驗的一點說明**：所有測驗都存放在 Quiz-app 資料夾中，路徑為 etc\quiz-app，或者可以[在線訪問這裡](https://ff-quizzes.netlify.app/)。這些測驗已經在課程中進行了連結。測驗應用程式可以在本地運行，也可以部署到 Azure；請按照 `quiz-app` 資料夾中的指示操作。測驗內容正在逐步進行本地化。
## 尋求協助
> **關於測驗的說明**：所有測驗都存放在 etc\quiz-app 的 Quiz-app 資料夾中，或可在[線上查看](https://ff-quizzes.netlify.app/)。它們已在課程中連結，測驗應用程式可以在本地執行或部署到 Azure；請按照 `quiz-app` 資料夾中的指示操作。測驗正在逐步進行本地化。
## 幫助需求
您有任何建議或發現拼寫或程式碼錯誤嗎？請提出問題或建立拉取請求。
您有任何建議或發現拼寫或程式碼錯誤嗎？請提交一個問題或建立一個拉取請求。
## 特別感謝
@ -145,7 +145,7 @@ CO_OP_TRANSLATOR_METADATA:
## 其他課程
我們的團隊還製作了其他課程！查看以下內容：
我們的團隊還製作了其他課程！請查看以下內容：
- [生成式 AI 初學者課程](https://aka.ms/genai-beginners)
- [生成式 AI 初學者課程 .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
@ -158,11 +158,11 @@ CO_OP_TRANSLATOR_METADATA:
- [網頁開發初學者課程](https://aka.ms/webdev-beginners)
- [物聯網初學者課程](https://aka.ms/iot-beginners)
- [XR 開發初學者課程](https://github.com/microsoft/xr-development-for-beginners)
- [精通 GitHub Copilot 用於代理性使用](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [精通 GitHub Copilot 用於 C#/.NET 開發者](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [精通 GitHub Copilot 的智能應用](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [精通 GitHub Copilot 的 C#/.NET 開發者課程](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [選擇你的 Copilot 冒險](https://github.com/microsoft/CopilotAdventures)
---
**免責聲明**：
本文件已使用 AI 翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。儘管我們致力於提供準確的翻譯，請注意自動翻譯可能包含錯誤或不準確之處。原始文件的母語版本應被視為權威來源。對於關鍵資訊，建議使用專業人工翻譯。我們對因使用此翻譯而引起的任何誤解或錯誤解釋不承擔責任。
本文件使用 AI 翻譯服務 [Co-op Translator](https://github.com/Azure/co-op-translator) 進行翻譯。我們致力於提供準確的翻譯，但請注意，自動翻譯可能包含錯誤或不準確之處。應以原始語言的文件作為權威來源。對於關鍵資訊，建議尋求專業人工翻譯。我們對因使用此翻譯而產生的任何誤解或錯誤解讀概不負責。

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|:---:|
| Штучний інтелект для початківців - _Скетчнот від [@girlie_mac](https://twitter.com/girlie_mac)_ |
Досліджуйте світ **Штучного інтелекту** (AI) за допомогою нашої 12-тижневої навчальної програми, що складається з 24 уроків! Вона включає практичні заняття, тести та лабораторні роботи. Програма розрахована на початківців і охоплює інструменти, такі як TensorFlow і PyTorch, а також етику в AI.
Досліджуйте світ **Штучного інтелекту** (AI) за допомогою нашої 12-тижневої навчальної програми, що складається з 24 уроків! Вона включає практичні заняття, вікторини та лабораторні роботи. Програма розрахована на початківців і охоплює інструменти, такі як TensorFlow і PyTorch, а також етику в AI.
### 🌐 Підтримка багатомовності
@ -48,7 +48,7 @@ CO_OP_TRANSLATOR_METADATA:
* Різні підходи до Штучного інтелекту, включаючи "старий добрий" символічний підхід із **Представленням знань** та логікою ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Нейронні мережі** та **Глибоке навчання**, які є основою сучасного AI. Ми пояснимо концепції цих важливих тем за допомогою коду в двох найпопулярніших фреймворках - [TensorFlow](http://Tensorflow.org) та [PyTorch](http://pytorch.org).
* **Нейронні архітектури** для роботи з зображеннями та текстом. Ми розглянемо сучасні моделі, хоча деякі з них можуть бути не найновішими.
* **Нейронні архітектури** для роботи з зображеннями та текстом. Ми розглянемо сучасні моделі, хоча вони можуть бути трохи застарілими порівняно з найновішими розробками.
* Менш популярні підходи до AI, такі як **Генетичні алгоритми** та **Системи з багатьма агентами**.
Що ми не будемо охоплювати в цій навчальній програмі:
@ -56,13 +56,13 @@ CO_OP_TRANSLATOR_METADATA:
> [Знайдіть усі додаткові ресурси для цього курсу в нашій колекції Microsoft Learn](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Бізнес-кейси використання **AI у бізнесі**. Рекомендуємо пройти навчальний шлях [Вступ до AI для бізнес-користувачів](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) на Microsoft Learn або [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), розроблений у співпраці з [INSEAD](https://www.insead.edu/).
* **Класичне машинне навчання**, яке добре описане в нашій [Навчальній програмі з машинного навчання для початківців](http://github.com/Microsoft/ML-for-Beginners).
* Практичні застосування AI, побудовані за допомогою **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Для цього рекомендуємо почати з модулів Microsoft Learn для [комп'ютерного зору](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [обробки природної мови](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Генеративного AI з Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** та інших.
* **Класичне машинне навчання**, яке добре описане в нашій навчальній програмі [Машинне навчання для початківців](http://github.com/Microsoft/ML-for-Beginners).
* Практичні застосування AI, побудовані за допомогою **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Для цього рекомендуємо почати з модулів Microsoft Learn для [зору](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [обробки природної мови](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Генеративного AI з Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** та інших.
* Специфічні ML **хмарні фреймворки**, такі як [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) або [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Рекомендуємо пройти навчальні шляхи [Створення та управління рішеннями машинного навчання з Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) та [Створення та управління рішеннями машинного навчання з Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **Розмовний AI** та **чат-боти**. Є окремий навчальний шлях [Створення рішень для розмовного AI](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), а також можна звернутися до [цієї статті](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) для отримання додаткової інформації.
* **Глибока математика**, що лежить в основі глибокого навчання. Для цього рекомендуємо книгу [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) авторів Іана Гудфеллоу, Йошуа Бенджіо та Аарона Курвіля, яка також доступна онлайн за адресою [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Для м'якого вступу до тем _AI у хмарі_ рекомендуємо пройти навчальний шлях [Початок роботи зі штучним інтелектом на Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
Для м'якого вступу до тем _AI у хмарі_ можна пройти навчальний шлях [Початок роботи зі штучним інтелектом на Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Зміст
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| I | [**Вступ до AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Вступ та історія AI](./lessons/1-Intro/README.md) | - | - |
| II | **Символічний AI** |
| 02 | [Представлення знань та експертні системи](./lessons/2-Symbolic/README.md) | [Експертні системи](./lessons/2-Symbolic/Animals.ipynb) / [Онтологія](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Граф концептів](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| 02 | [Представлення знань та експертні системи](./lessons/2-Symbolic/README.md) | [Експертні системи](./lessons/2-Symbolic/Animals.ipynb) / [Онтологія](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Граф концепцій](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Вступ до нейронних мереж**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Перцептрон](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Ноутбук](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Лабораторна робота](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Багатошаровий перцептрон та створення власного фреймворку](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Ноутбук](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Лабораторна робота](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Вступ до фреймворків (PyTorch/TensorFlow) та перенавчання](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лабораторна робота](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Комп'ютерний зір**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Дослідження комп'ютерного зору на Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Вступ до комп'ютерного зору. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Ноутбук](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Лабораторна робота](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| IV | [**Комп'ютерне бачення**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Дослідження комп'ютерного бачення на Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Вступ до комп'ютерного бачення. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Ноутбук](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Лабораторна робота](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Згорткові нейронні мережі](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Архітектури CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Лабораторна робота](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Попередньо навчені мережі та трансферне навчання](./lessons/4-ComputerVision/08-TransferLearning/README.md) та [Трюки навчання](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лабораторна робота](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Автоенкодери та варіаційні автоенкодери (VAEs)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Генеративно-змагальні мережі (GANs) та перенесення художнього стилю](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 08 | [Попередньо навчені мережі та перенесення навчання](./lessons/4-ComputerVision/08-TransferLearning/README.md) та [Трюки навчання](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Лабораторна робота](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Автокодувальники та VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Генеративні змагальні мережі та перенесення художнього стилю](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Виявлення об'єктів](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Лабораторна робота](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Семантична сегментація. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Обробка природної мови**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Дослідження обробки природної мови на Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Представлення тексту. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Семантичні векторні представлення слів. Word2Vec та GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Моделювання мови. Навчання власних векторних представлень](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Лабораторна робота](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Рекурентні нейронні мережі](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Генеративні рекурентні мережі](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Лабораторна робота](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Трансформери. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Розпізнавання іменованих сутностей (NER)](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Лабораторна робота](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Великі мовні моделі, програмування підказок та задачі з малим числом прикладів](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [Представлення тексту. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Семантичні векторні представлення слів. Word2Vec та GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Моделювання мови. Навчання власних векторних представлень](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Лабораторна робота](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Рекурентні нейронні мережі](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Генеративні рекурентні мережі](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Лабораторна робота](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Трансформери. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Розпізнавання іменованих сутностей](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Лабораторна робота](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Великі мовні моделі, програмування підказок та задачі з малим обсягом даних](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Інші техніки штучного інтелекту** || |
| 21 | [Генетичні алгоритми](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Ноутбук](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Глибоке підкріплювальне навчання](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Лабораторна робота](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 22 | [Глибоке навчання з підкріпленням](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Лабораторна робота](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Системи з багатьма агентами](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Етика штучного інтелекту** | | |
| 24 | [Етика штучного інтелекту та відповідальний AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Принципи відповідального AI](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
@ -105,14 +105,14 @@ CO_OP_TRANSLATOR_METADATA:
## Кожен урок містить
* Матеріали для попереднього ознайомлення
* Виконувані Jupyter-ноутбуки, які часто специфічні для фреймворку (**PyTorch** або **TensorFlow**). Виконуваний ноутбук також містить багато теоретичного матеріалу, тому для розуміння теми потрібно пройти хоча б одну версію ноутбука (або PyTorch, або TensorFlow).
* **Лабораторні роботи**, доступні для деяких тем, які дають можливість застосувати вивчений матеріал до конкретної задачі.
* Деякі розділи містять посилання на модулі [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum), які охоплюють пов’язані теми.
* Матеріали для попереднього читання
* Виконувані Jupyter Notebooks, які часто специфічні для фреймворку (**PyTorch** або **TensorFlow**). Виконуваний ноутбук також містить багато теоретичного матеріалу, тому для розуміння теми потрібно пройти хоча б одну версію ноутбука (або PyTorch, або TensorFlow).
* **Лабораторні роботи**, доступні для деяких тем, які дають можливість застосувати матеріал, який ви вивчили, до конкретної задачі.
* Деякі розділи містять посилання на модулі [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum), які охоплюють пов'язані теми.
## Початок роботи
- Ми створили [урок з налаштування](./lessons/0-course-setup/setup.md), щоб допомогти вам налаштувати середовище розробки. - Для викладачів ми також створили [урок з налаштування навчальної програми](./lessons/0-course-setup/for-teachers.md)!
- Ми створили [урок налаштування](./lessons/0-course-setup/setup.md), щоб допомогти вам налаштувати середовище розробки. - Для викладачів ми також створили [урок налаштування навчальної програми](./lessons/0-course-setup/for-teachers.md)!
- Як [запустити код у VSCode або Codepace](./lessons/0-course-setup/how-to-run.md)
Виконайте ці кроки:
@ -121,16 +121,16 @@ CO_OP_TRANSLATOR_METADATA:
Клонуйте репозиторій: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Не забудьте додати зірочку (🌟) цьому репозиторію, щоб легше знайти його пізніше.
Не забудьте поставити зірочку (🌟) цьому репозиторію, щоб легше знайти його пізніше.
## Познайомтеся з іншими учнями
## Знайомтеся з іншими учнями
Приєднуйтесь до нашого [офіційного AI Discord-сервера](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), щоб познайомитися та спілкуватися з іншими учнями, які проходять цей курс, і отримати підтримку.
Приєднуйтесь до нашого [офіційного AI Discord сервера](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum), щоб зустрітися та спілкуватися з іншими учнями, які проходять цей курс, і отримати підтримку.
Якщо у вас є відгуки про продукт або запитання під час створення, відвідайте наш [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum)
## Тести
> **Примітка щодо вікторин**: Усі вікторини знаходяться в папці Quiz-app за шляхом etc\quiz-app, або [онлайн тут](https://ff-quizzes.netlify.app/). Вони пов’язані з уроками, і додаток для вікторин можна запускати локально або розгортати в Azure; дотримуйтесь інструкцій у папці `quiz-app`. Вікторини поступово локалізуються.
> **Примітка щодо вікторин**: Усі вікторини знаходяться в папці Quiz-app у etc\quiz-app, або [Онлайн тут](https://ff-quizzes.netlify.app/). Вони пов’язані з уроками, і додаток для вікторин можна запускати локально або розгортати на Azure; дотримуйтесь інструкцій у папці `quiz-app`. Вікторини поступово локалізуються.
## Потрібна допомога
Є пропозиції або знайшли орфографічні чи кодові помилки? Створіть issue або pull request.
@ -147,22 +147,22 @@ CO_OP_TRANSLATOR_METADATA:
Наша команда створює й інші навчальні матеріали! Ознайомтеся з ними:
- [Генеративний ШІ для початківців](https://aka.ms/genai-beginners)
- [Генеративний ШІ для початківців .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Генеративний ШІ з JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Генеративний ШІ з Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [ШІ для початківців](https://aka.ms/ai-beginners)
- [Наука про дані для початківців](https://aka.ms/datascience-beginners)
- [Машинне навчання для початківців](https://aka.ms/ml-beginners)
- [Generative AI для початківців](https://aka.ms/genai-beginners)
- [Generative AI для початківців .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI з JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI з Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI для початківців](https://aka.ms/ai-beginners)
- [Data Science для початківців](https://aka.ms/datascience-beginners)
- [ML для початківців](https://aka.ms/ml-beginners)
- [Кібербезпека для початківців](https://github.com/microsoft/Security-101)
- [Веб-розробка для початківців](https://aka.ms/webdev-beginners)
- [Інтернет речей для початківців](https://aka.ms/iot-beginners)
- [IoT для початківців](https://aka.ms/iot-beginners)
- [Розробка XR для початківців](https://github.com/microsoft/xr-development-for-beginners)
- [Опанування GitHub Copilot для агентного використання](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Опанування GitHub Copilot для розробників C#/.NET](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Обери свою пригоду з Copilot](https://github.com/microsoft/CopilotAdventures)
- [Вибери свою пригоду з Copilot](https://github.com/microsoft/CopilotAdventures)
---
**Відмова від відповідальності**:
Цей документ було перекладено за допомогою сервісу автоматичного перекладу [Co-op Translator](https://github.com/Azure/co-op-translator). Хоча ми прагнемо до точності, будь ласка, майте на увазі, що автоматичні переклади можуть містити помилки або неточності. Оригінальний документ на його рідній мові слід вважати авторитетним джерелом. Для критичної інформації рекомендується професійний людський переклад. Ми не несемо відповідальності за будь-які непорозуміння або неправильні тлумачення, що виникають внаслідок використання цього перекладу.
Цей документ був перекладений за допомогою сервісу автоматичного перекладу [Co-op Translator](https://github.com/Azure/co-op-translator). Хоча ми прагнемо до точності, будь ласка, майте на увазі, що автоматичні переклади можуть містити помилки або неточності. Оригінальний документ на його рідній мові слід вважати авторитетним джерелом. Для критичної інформації рекомендується професійний людський переклад. Ми не несемо відповідальності за будь-які непорозуміння або неправильні тлумачення, що виникають у результаті використання цього перекладу.

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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# مصنوعی ذہانت برائے ابتدائی افراد - ایک نصاب
# مصنوعی ذہانت کے ابتدائی کورس - نصاب
|![اسکیچ نوٹ از @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.ur.png)|
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.ur.png)|
|:---:|
| مصنوعی ذہانت برائے ابتدائی افراد - _اسکیچ نوٹ از [@girlie_mac](https://twitter.com/girlie_mac)_ |
| مصنوعی ذہانت کے ابتدائی کورس - _اسکیچ نوٹ [@girlie_mac](https://twitter.com/girlie_mac) کی جانب سے_ |
**مصنوعی ذہانت** (AI) کی دنیا کو دریافت کریں ہمارے 12 ہفتوں اور 24 اسباق پر مشتمل نصاب کے ساتھ! اس میں عملی اسباق، کوئزز، اور لیبز شامل ہیں۔ یہ نصاب ابتدائی افراد کے لیے موزوں ہے اور TensorFlow اور PyTorch جیسے ٹولز کے ساتھ ساتھ AI میں اخلاقیات کا احاطہ کرتا ہے۔
**مصنوعی ذہانت** (AI) کی دنیا کو دریافت کریں ہمارے 12 ہفتوں کے 24 اسباق پر مشتمل نصاب کے ساتھ! اس میں عملی اسباق، کوئز اور لیبز شامل ہیں۔ یہ نصاب ابتدائی افراد کے لیے موزوں ہے اور TensorFlow اور PyTorch جیسے ٹولز کے ساتھ ساتھ AI کے اخلاقیات پر بھی روشنی ڈالتا ہے۔
### 🌐 کثیر لسانی معاونت
### 🌐 کثیر زبان کی حمایت
#### GitHub ایکشن کے ذریعے معاونت (خودکار اور ہمیشہ تازہ ترین)
#### GitHub ایکشن کے ذریعے خودکار اور ہمیشہ تازہ ترین
[فرانسیسی](../fr/README.md) | [ہسپانوی](../es/README.md) | [جرمن](../de/README.md) | [روسی](../ru/README.md) | [عربی](../ar/README.md) | [فارسی](../fa/README.md) | [اردو](./README.md) | [چینی (آسان)](../zh/README.md) | [چینی (روایتی، مکاؤ)](../mo/README.md) | [چینی (روایتی، ہانگ کانگ)](../hk/README.md) | [چینی (روایتی، تائیوان)](../tw/README.md) | [جاپانی](../ja/README.md) | [کوریائی](../ko/README.md) | [ہندی](../hi/README.md) | [بنگالی](../bn/README.md) | [مراٹھی](../mr/README.md) | [نیپالی](../ne/README.md) | [پنجابی (گرمکھی)](../pa/README.md) | [پرتگالی (پرتگال)](../pt/README.md) | [پرتگالی (برازیل)](../br/README.md) | [اطالوی](../it/README.md) | [پولش](../pl/README.md) | [ترکی](../tr/README.md) | [یونانی](../el/README.md) | [تھائی](../th/README.md) | [سویڈش](../sv/README.md) | [ڈینش](../da/README.md) | [نارویجین](../no/README.md) | [فنش](../fi/README.md) | [ڈچ](../nl/README.md) | [عبرانی](../he/README.md) | [ویتنامی](../vi/README.md) | [انڈونیشیائی](../id/README.md) | [ملائی](../ms/README.md) | [ٹیگالوگ (فلپائنی)](../tl/README.md) | [سواحلی](../sw/README.md) | [ہنگری](../hu/README.md) | [چیک](../cs/README.md) | [سلوواک](../sk/README.md) | [رومانیائی](../ro/README.md) | [بلغاریائی](../bg/README.md) | [سربیائی (سیریلیک)](../sr/README.md) | [کروشین](../hr/README.md) | [سلووینیائی](../sl/README.md) | [یوکرینیائی](../uk/README.md) | [برمی (میانمار)](../my/README.md)
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**اگر آپ اضافی زبانوں میں ترجمہ چاہتے ہیں تو معاون زبانوں کی فہرست [یہاں](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) دستیاب ہے۔**
**اگر آپ اضافی زبانوں میں ترجمہ چاہتے ہیں تو دستیاب زبانوں کی فہرست [یہاں](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) موجود ہے۔**
## کمیونٹی میں شامل ہوں
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
@ -44,35 +44,35 @@ CO_OP_TRANSLATOR_METADATA:
**[کورس کا مائنڈ میپ](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
اس نصاب میں، آپ سیکھیں گے:
اس نصاب میں آپ سیکھیں گے:
* مصنوعی ذہانت کے مختلف طریقے، بشمول "پرانا" علامتی طریقہ **علم کی نمائندگی** اور استدلال ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))۔
* **نیورل نیٹ ورکس** اور **ڈیپ لرننگ**، جو جدید AI کا مرکز ہیں۔ ہم ان اہم موضوعات کے پیچھے تصورات کو دو مشہور فریم ورکس - [TensorFlow](http://Tensorflow.org) اور [PyTorch](http://pytorch.org) - کے ذریعے کوڈ کے ساتھ واضح کریں گے۔
* **نیورل آرکیٹیکچرز** جو تصاویر اور متن کے ساتھ کام کرتے ہیں۔ ہم حالیہ ماڈلز کا احاطہ کریں گے لیکن جدید ترین میں کچھ کمی ہو سکتی ہے۔
* کم مقبول AI طریقے، جیسے **جینیٹک الگورتھمز** اور **ملٹی ایجنٹ سسٹمز**۔
* مصنوعی ذہانت کے مختلف طریقے، جن میں "پرانا اچھا" علامتی طریقہ شامل ہے جیسے **علم کی نمائندگی** اور استدلال ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))۔
* **نیورل نیٹ ورکس** اور **ڈیپ لرننگ**، جو جدید AI کے مرکز میں ہیں۔ ہم ان اہم موضوعات کے پیچھے تصورات کو دو مشہور فریم ورک - [TensorFlow](http://Tensorflow.org) اور [PyTorch](http://pytorch.org) کے کوڈ کے ذریعے واضح کریں گے۔
* **نیورل آرکیٹیکچرز** جو تصاویر اور متن کے ساتھ کام کرتے ہیں۔ ہم حالیہ ماڈلز کا احاطہ کریں گے لیکن جدید ترین ماڈلز میں کچھ کمی ہو سکتی ہے۔
* کم مشہور AI طریقے، جیسے **جینیٹک الگورتھمز** اور **ملٹی ایجنٹ سسٹمز**۔
ہم اس نصاب میں کیا شامل نہیں کریں گے:
> [اس کورس کے تمام اضافی وسائل ہماری Microsoft Learn کلیکشن میں تلاش کریں](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **کاروبار میں AI کے استعمال کے کیسز**۔ [کاروباری صارفین کے لیے AI کا تعارف](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) یا [AI بزنس اسکول](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) پر غور کریں، جو [INSEAD](https://www.insead.edu/) کے تعاون سے تیار کیا گیا ہے۔
* **کلاسیکی مشین لرننگ**، جو ہمارے [مشین لرننگ برائے ابتدائی افراد کے نصاب](http://github.com/Microsoft/ML-for-Beginners) میں اچھی طرح بیان کی گئی ہے۔
* **[کگنیٹیو سروسز](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** کا استعمال کرتے ہوئے عملی AI ایپلیکیشنز۔ اس کے لیے، ہم تجویز کرتے ہیں کہ آپ Microsoft Learn کے ماڈیولز سے آغاز کریں جیسے [ویژن](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)، [قدرتی زبان کی پروسیسنگ](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)، **[Azure OpenAI سروس کے ساتھ جنریٹو AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** اور دیگر۔
* مخصوص ML **کلاؤڈ فریم ورکس**، جیسے [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)، [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)، یا [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)۔
* **بات چیت پر مبنی AI** اور **چیٹ بوٹس**۔ اس کے لیے ایک علیحدہ [بات چیت پر مبنی AI حل بنائیں](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) لرننگ پاتھ موجود ہے، اور آپ مزید تفصیل کے لیے [یہ بلاگ پوسٹ](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) بھی دیکھ سکتے ہیں۔
* **ڈیپ لرننگ کے پیچھے گہری ریاضی**۔ اس کے لیے، ہم تجویز کرتے ہیں [ڈیپ لرننگ](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) از ایان گڈفیلو، یوشوا بینگیو اور آرون کورویل، جو آن لائن بھی دستیاب ہے [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)۔
* **AI کا کاروبار میں استعمال** کے کاروباری کیسز۔ [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) یا [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) پر غور کریں، جو [INSEAD](https://www.insead.edu/) کے تعاون سے تیار کیا گیا ہے۔
* **کلاسک مشین لرننگ**، جو ہمارے [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners) میں اچھی طرح بیان کی گئی ہے۔
* **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** کے ذریعے بنائے گئے عملی AI ایپلیکیشنز۔ اس کے لیے ہم تجویز کرتے ہیں کہ آپ Microsoft Learn کے ماڈیولز جیسے [vision](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)، [natural language processing](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)، **[Generative AI with Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** اور دیگر سے آغاز کریں۔
* مخصوص ML **کلاؤڈ فریم ورک**، جیسے [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)، [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum)، یا [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)۔ [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) اور [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) لرننگ پاتھز پر غور کریں۔
* **بات چیت کی AI** اور **چیٹ بوٹس**۔ اس کے لیے الگ [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) لرننگ پاتھ موجود ہے، اور آپ مزید تفصیل کے لیے [اس بلاگ پوسٹ](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) کا حوالہ دے سکتے ہیں۔
* **ڈیپ لرننگ کے پیچھے گہری ریاضی**۔ اس کے لیے ہم تجویز کرتے ہیں [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) از ایان گڈفیلو، یوشوا بینگیو اور ایرون کورویل، جو آن لائن بھی دستیاب ہے [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)۔
_کلاؤڈ میں AI_ کے موضوعات کا نرم تعارف حاصل کرنے کے لیے آپ [Azure پر مصنوعی ذہانت کے ساتھ شروعات کریں](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) لرننگ پاتھ لے سکتے ہیں۔
کلاؤڈ میں _AI_ کے موضوعات کے لیے نرم تعارف کے لیے آپ [Get started with artificial intelligence on Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) لرننگ پاتھ پر غور کر سکتے ہیں۔
# مواد
| | سبق کا لنک | PyTorch/Keras/TensorFlow | لیب |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [کورس سیٹ اپ](./lessons/0-course-setup/setup.md) | [اپنے ڈیولپمنٹ ماحول کو سیٹ اپ کریں](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI کا تعارف**](./lessons/1-Intro/README.md) | | |
| 01 | [AI کا تعارف اور تاریخ](./lessons/1-Intro/README.md) | - | - |
| 0 | [کورس سیٹ اپ](./lessons/0-course-setup/setup.md) | [اپنا ڈیولپمنٹ ماحول سیٹ کریں](./lessons/0-course-setup/how-to-run.md) | |
| I | [**مصنوعی ذہانت کا تعارف**](./lessons/1-Intro/README.md) | | |
| 01 | [مصنوعی ذہانت کا تعارف اور تاریخ](./lessons/1-Intro/README.md) | - | - |
| II | **علامتی AI** |
| 02 | [علم کی نمائندگی اور ماہر نظام](./lessons/2-Symbolic/README.md) | [ماہر نظام](./lessons/2-Symbolic/Animals.ipynb) / [اونٹولوجی](./lessons/2-Symbolic/FamilyOntology.ipynb) /[تصوری گراف](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| 02 | [علم کی نمائندگی اور ماہر نظام](./lessons/2-Symbolic/README.md) | [ماہر نظام](./lessons/2-Symbolic/Animals.ipynb) / [اونٹولوجی](./lessons/2-Symbolic/FamilyOntology.ipynb) /[تصوراتی گراف](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**نیورل نیٹ ورکس کا تعارف**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [پرسپٹرون](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [نوٹ بک](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [لیب](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [ملٹی لیئرڈ پرسپٹرون اور اپنا فریم ورک بنانا](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [نوٹ بک](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [لیب](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
@ -86,17 +86,17 @@ _کلاؤڈ میں AI_ کے موضوعات کا نرم تعارف حاصل کر
| 11 | [آبجیکٹ ڈیٹیکشن](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [لیب](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [سیمینٹک سیگمنٹیشن۔ U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**نیچرل لینگویج پروسیسنگ**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Microsoft Azure پر نیچرل لینگویج پروسیسنگ کو دریافت کریں](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [ٹیکسٹ ریپریزنٹیشن۔ Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [سیمینٹک ورڈ ایمبیڈنگز۔ Word2Vec اور GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [لینگویج ماڈلنگ۔ اپنے ایمبیڈنگز کو ٹرین کریں](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [لیب](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [ریکَرَنٹ نیورل نیٹ ورکس](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [جنریٹو ریکَرَنٹ نیٹ ورکس](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [لیب](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ٹرانسفارمرز۔ BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [نامزد ادارہ پہچان](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [لیب](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [بڑے لینگویج ماڈلز، پرامپٹ پروگرامنگ اور فیو شاٹ ٹاسکس](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| 13 | [ٹیکسٹ ریپریزنٹیشن۔ Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [سیمینٹک ورڈ ایمبیڈنگز۔ Word2Vec اور GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [لینگویج ماڈلنگ۔ اپنے ایمبیڈنگز کو ٹرین کریں](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [لیب](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [ریکرنٹ نیورل نیٹ ورکس](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [جنریٹو ریکرنٹ نیٹ ورکس](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [لیب](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [ٹرانسفارمرز۔ BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [نامزد ادارہ کی شناخت](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [لیب](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [بڑے لینگویج ماڈلز، پرامپٹ پروگرامنگ اور فیو شاٹ ٹاسکس](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **دیگر AI تکنیکیں** || |
| 21 | [جینیٹک الگورتھمز](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [نوٹ بک](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [ڈیپ ریئنفورسمنٹ لرننگ](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [لیب](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 22 | [ڈیپ ری انفورسمنٹ لرننگ](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [لیب](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [ملٹی ایجنٹ سسٹمز](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI اخلاقیات** | | |
| 24 | [AI اخلاقیات اور ذمہ دار AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: ذمہ دار AI اصول](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
@ -110,59 +110,59 @@ _کلاؤڈ میں AI_ کے موضوعات کا نرم تعارف حاصل کر
* **لیبز** کچھ موضوعات کے لیے دستیاب ہیں، جو آپ کو سیکھے گئے مواد کو کسی خاص مسئلے پر لاگو کرنے کا موقع فراہم کرتی ہیں۔
* کچھ سیکشنز میں [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) ماڈیولز کے لنکس شامل ہیں جو متعلقہ موضوعات کا احاطہ کرتے ہیں۔
## شروعات کریں
## شروع کریں
- ہم نے آپ کے ترقیاتی ماحول کو ترتیب دینے میں مدد کے لیے ایک [سیٹ اپ سبق](./lessons/0-course-setup/setup.md) بنایا ہے۔ - اساتذہ کے لیے، ہم نے آپ کے لیے بھی ایک [نصاب سیٹ اپ سبق](./lessons/0-course-setup/for-teachers.md) بنایا ہے!
- کوڈ کو [VSCode یا Codepace میں کیسے چلائیں](./lessons/0-course-setup/how-to-run.md)
- کوڈ کو VSCode یا Codepace میں [چلانے کا طریقہ](./lessons/0-course-setup/how-to-run.md)
یہ اقدامات کریں:
ریپوزیٹری کو فورک کریں: اس صفحے کے اوپر دائیں کونے میں "Fork" بٹن پر کلک کریں۔
ریپوزٹری کو فورک کریں: اس صفحے کے اوپر دائیں کونے میں "Fork" بٹن پر کلک کریں۔
ریپوزیٹری کو کلون کریں: `git clone https://github.com/microsoft/AI-For-Beginners.git`
ریپوزٹری کو کلون کریں: `git clone https://github.com/microsoft/AI-For-Beginners.git`
اس ریپو کو اسٹار (🌟) کرنا نہ بھولیں تاکہ بعد میں اسے آسانی سے تلاش کر سکیں۔
## دیگر سیکھنے والوں سے ملیں
## دیگر سیکھنے والوں سے ملاقات کریں
ہمارے [سرکاری AI Discord سرور](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) میں شامل ہوں تاکہ اس کورس کو لینے والے دیگر سیکھنے والوں سے ملاقات کریں اور نیٹ ورک کریں اور مدد حاصل کریں۔
اگر آپ کے پاس پروڈکٹ فیڈبیک یا سوالات ہیں تو ہمارے [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) پر جائیں۔
اگر آپ کے پاس پروڈکٹ فیڈبیک یا سوالات ہیں تو [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) پر جائیں۔
## کوئزز
> **کوئزز کے بارے میں ایک نوٹ**: تمام کوئزز Quiz-app فولڈر میں etc\quiz-app کے اندر موجود ہیں، یا [یہاں آن لائن دستیاب ہیں](https://ff-quizzes.netlify.app/)۔ یہ اسباق کے اندر سے منسلک ہیں۔ کوئز ایپ کو مقامی طور پر چلایا جا سکتا ہے یا Azure پر ڈپلائے کیا جا سکتا ہے؛ `quiz-app` فولڈر میں دی گئی ہدایات پر عمل کریں۔ یہ بتدریج مقامی زبان میں ترجمہ کیے جا رہے ہیں۔
> **کوئزز کے بارے میں ایک نوٹ**: تمام کوئزز Quiz-app فولڈر میں etc\quiz-app میں موجود ہیں، یا [آن لائن یہاں](https://ff-quizzes.netlify.app/)۔ یہ اسباق کے اندر سے لنک کیے گئے ہیں۔ کوئز ایپ کو مقامی طور پر چلایا جا سکتا ہے یا Azure پر تعینات کیا جا سکتا ہے؛ `quiz-app` فولڈر میں دی گئی ہدایات پر عمل کریں۔ یہ بتدریج مقامی زبان میں منتقل کیے جا رہے ہیں۔
## مدد درکار ہے
کیا آپ کے پاس تجاویز ہیں یا آپ نے ہجے یا کوڈ کی غلطیاں تلاش کی ہیں؟ ایک مسئلہ اٹھائیں یا پل ریکویسٹ بنائیں۔
کیا آپ کے پاس تجاویز ہیں یا آپ نے ہجے یا کوڈ کی غلطیاں تلاش کی ہیں؟ ایک مسئلہ اٹھائیں یا ایک پل ریکویسٹ بنائیں۔
## خصوصی شکریہ
* **✍️ مرکزی مصنف:** [دیمتری سوشنیکوف](http://soshnikov.com)، پی ایچ ڈی
* **🔥 ایڈیٹر:** [جین لوپر](https://twitter.com/jenlooper)، پی ایچ ڈی
* **🎨 اسکیچ نوٹ آرٹسٹ:** [تومومی ایمورا](https://twitter.com/girlie_mac)
* **✅ کوئز تخلیق کار:** [لطیفہ بیلو](https://github.com/CinnamonXI)، [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 مرکزی شراکت دار:** [ایوگینی پیشچک](https://github.com/Pe4enIks)
* **✍️ بنیادی مصنف:** [Dmitry Soshnikov](http://soshnikov.com)، پی ایچ ڈی
* **🔥 ایڈیٹر:** [Jen Looper](https://twitter.com/jenlooper)، پی ایچ ڈی
* **🎨 اسکیچ نوٹ مصور:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ کوئز تخلیق کار:** [Lateefah Bello](https://github.com/CinnamonXI)، [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 بنیادی شراکت دار:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## دیگر نصاب
ہماری ٹیم دیگر نصاب بھی تیار کرتی ہے! دیکھیں:
- [ابتدائیوں کے لیے جنریٹو AI](https://aka.ms/genai-beginners)
- [ابتدائیوں کے لیے جنریٹو AI .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [جاوا اسکرپٹ کے ساتھ جنریٹو AI](https://github.com/microsoft/generative-ai-with-javascript)
- [جاوا کے ساتھ جنریٹو AI](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [ابتدائیوں کے لیے AI](https://aka.ms/ai-beginners)
- [ابتدائیوں کے لیے ڈیٹا سائنس](https://aka.ms/datascience-beginners)
- [ابتدائیوں کے لیے مشین لرننگ](https://aka.ms/ml-beginners)
- [ابتدائیوں کے لیے سائبر سیکیورٹی](https://github.com/microsoft/Security-101)
- [ابتدائیوں کے لیے ویب ڈویلپمنٹ](https://aka.ms/webdev-beginners)
- [ابتدائیوں کے لیے IoT](https://aka.ms/iot-beginners)
- [ابتدائیوں کے لیے XR ڈویلپمنٹ](https://github.com/microsoft/xr-development-for-beginners)
- [ایجنٹک استعمال کے لیے GitHub Copilot میں مہارت حاصل کریں](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [C#/.NET ڈویلپرز کے لیے GitHub Copilot میں مہارت حاصل کریں](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [اپنی Copilot ایڈونچر کا انتخاب کریں](https://github.com/microsoft/CopilotAdventures)
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [Generative AI with JavaScript](https://github.com/microsoft/generative-ai-with-javascript)
- [Generative AI with Java](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI for Beginners](https://aka.ms/ai-beginners)
- [Data Science for Beginners](https://aka.ms/datascience-beginners)
- [ML for Beginners](https://aka.ms/ml-beginners)
- [Cybersecurity for Beginners](https://github.com/microsoft/Security-101)
- [Web Dev for Beginners](https://aka.ms/webdev-beginners)
- [IoT for Beginners](https://aka.ms/iot-beginners)
- [XR Development for Beginners](https://github.com/microsoft/xr-development-for-beginners)
- [Mastering GitHub Copilot for Agentic use](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [Mastering GitHub Copilot for C#/.NET Developers](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [Choose Your Own Copilot Adventure](https://github.com/microsoft/CopilotAdventures)
---
**ڈسکلیمر**:
یہ دستاویز AI ترجمہ سروس [Co-op Translator](https://github.com/Azure/co-op-translator) کا استعمال کرتے ہوئے ترجمہ کی گئی ہے۔ ہم درستگی کے لیے کوشش کرتے ہیں، لیکن براہ کرم آگاہ رہیں کہ خودکار ترجمے میں غلطیاں یا عدم درستگی ہو سکتی ہیں۔ اصل دستاویز کو اس کی اصل زبان میں مستند ذریعہ سمجھا جانا چاہیے۔ اہم معلومات کے لیے، پیشہ ور انسانی ترجمہ کی سفارش کی جاتی ہے۔ اس ترجمے کے استعمال سے پیدا ہونے والی کسی بھی غلط فہمی یا غلط تشریح کے لیے ہم ذمہ دار نہیں ہیں۔
یہ دستاویز AI ترجمہ سروس [Co-op Translator](https://github.com/Azure/co-op-translator) کا استعمال کرتے ہوئے ترجمہ کی گئی ہے۔ ہم درستگی کے لیے کوشش کرتے ہیں، لیکن براہ کرم آگاہ رہیں کہ خودکار ترجمے میں غلطیاں یا غیر درستیاں ہو سکتی ہیں۔ اصل دستاویز کو اس کی اصل زبان میں مستند ذریعہ سمجھا جانا چاہیے۔ اہم معلومات کے لیے، پیشہ ور انسانی ترجمہ کی سفارش کی جاتی ہے۔ ہم اس ترجمے کے استعمال سے پیدا ہونے والی کسی بھی غلط فہمی یا غلط تشریح کے ذمہ دار نہیں ہیں۔

132
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@ -1,21 +1,21 @@
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"original_hash": "07191303b7ea2aff1d47e2b0fe4bb862",
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[![Người đóng góp GitHub](https://img.shields.io/github/contributors/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/graphs/contributors/)
[![Vấn đề GitHub](https://img.shields.io/github/issues/microsoft/AI-For-Beginners.svg)](https://GitHub.com/microsoft/AI-For-Beginners/issues/)
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[![Sao GitHub](https://img.shields.io/github/stars/microsoft/AI-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/AI-For-Beginners/stargazers/)
[![GitHub watchers](https://img.shields.io/github/watchers/microsoft/AI-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/AI-For-Beginners/watchers/)
[![GitHub forks](https://img.shields.io/github/forks/microsoft/AI-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/AI-For-Beginners/network/)
[![GitHub stars](https://img.shields.io/github/stars/microsoft/AI-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/AI-For-Beginners/stargazers/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/microsoft/ai-for-beginners/HEAD)
[![Gitter](https://badges.gitter.im/Microsoft/ai-for-beginners.svg)](https://gitter.im/Microsoft/ai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
@ -23,96 +23,96 @@ CO_OP_TRANSLATOR_METADATA:
# Trí tuệ nhân tạo cho người mới bắt đầu - Một chương trình học
|![Sketchnote của @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.vi.png)|
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.vi.png)|
|:---:|
| AI For Beginners - _Sketchnote của [@girlie_mac](https://twitter.com/girlie_mac)_ |
| AI For Beginners - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ |
Khám phá thế giới **Trí tuệ Nhân tạo** (AI) với chương trình học kéo dài 12 tuần, gồm 24 bài học của chúng tôi! Chương trình bao gồm các bài học thực hành, câu đố và phòng thí nghiệm. Đây là chương trình thân thiện với người mới bắt đầu, bao gồm các công cụ như TensorFlow và PyTorch, cũng như các vấn đề đạo đức trong AI.
Khám phá thế giới **Trí tuệ nhân tạo** (AI) với chương trình học kéo dài 12 tuần, gồm 24 bài học! Chương trình bao gồm các bài học thực hành, bài kiểm tra và phòng thí nghiệm. Nội dung thân thiện với người mới bắt đầu và bao gồm các công cụ như TensorFlow và PyTorch, cũng như các vấn đề đạo đức trong AI.
### 🌐 Hỗ trợ đa ngôn ngữ
#### Được hỗ trợ qua GitHub Action (Tự động & Luôn cập nhật)
[Tiếng Pháp](../fr/README.md) | [Tiếng Tây Ban Nha](../es/README.md) | [Tiếng Đức](../de/README.md) | [Tiếng Nga](../ru/README.md) | [Tiếng Ả Rập](../ar/README.md) | [Tiếng Ba Tư (Farsi)](../fa/README.md) | [Tiếng Urdu](../ur/README.md) | [Tiếng Trung (Giản thể)](../zh/README.md) | [Tiếng Trung (Phồn thể, Macau)](../mo/README.md) | [Tiếng Trung (Phồn thể, Hồng Kông)](../hk/README.md) | [Tiếng Trung (Phồn thể, Đài Loan)](../tw/README.md) | [Tiếng Nhật](../ja/README.md) | [Tiếng Hàn](../ko/README.md) | [Tiếng Hindi](../hi/README.md) | [Tiếng Bengal](../bn/README.md) | [Tiếng Marathi](../mr/README.md) | [Tiếng Nepal](../ne/README.md) | [Tiếng Punjab (Gurmukhi)](../pa/README.md) | [Tiếng Bồ Đào Nha (Bồ Đào Nha)](../pt/README.md) | [Tiếng Bồ Đào Nha (Brazil)](../br/README.md) | [Tiếng Ý](../it/README.md) | [Tiếng Ba Lan](../pl/README.md) | [Tiếng Thổ Nhĩ Kỳ](../tr/README.md) | [Tiếng Hy Lạp](../el/README.md) | [Tiếng Thái](../th/README.md) | [Tiếng Thụy Điển](../sv/README.md) | [Tiếng Đan Mạch](../da/README.md) | [Tiếng Na Uy](../no/README.md) | [Tiếng Phần Lan](../fi/README.md) | [Tiếng Hà Lan](../nl/README.md) | [Tiếng Do Thái](../he/README.md) | [Tiếng Việt](./README.md) | [Tiếng Indonesia](../id/README.md) | [Tiếng Mã Lai](../ms/README.md) | [Tiếng Tagalog (Philippines)](../tl/README.md) | [Tiếng Swahili](../sw/README.md) | [Tiếng Hungary](../hu/README.md) | [Tiếng Séc](../cs/README.md) | [Tiếng Slovak](../sk/README.md) | [Tiếng Romania](../ro/README.md) | [Tiếng Bulgaria](../bg/README.md) | [Tiếng Serbia (Cyrillic)](../sr/README.md) | [Tiếng Croatia](../hr/README.md) | [Tiếng Slovenia](../sl/README.md) | [Tiếng Ukraina](../uk/README.md) | [Tiếng Myanmar (Miến Điện)](../my/README.md)
[French](../fr/README.md) | [Spanish](../es/README.md) | [German](../de/README.md) | [Russian](../ru/README.md) | [Arabic](../ar/README.md) | [Persian (Farsi)](../fa/README.md) | [Urdu](../ur/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Japanese](../ja/README.md) | [Korean](../ko/README.md) | [Hindi](../hi/README.md) | [Bengali](../bn/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Portuguese (Brazil)](../br/README.md) | [Italian](../it/README.md) | [Polish](../pl/README.md) | [Turkish](../tr/README.md) | [Greek](../el/README.md) | [Thai](../th/README.md) | [Swedish](../sv/README.md) | [Danish](../da/README.md) | [Norwegian](../no/README.md) | [Finnish](../fi/README.md) | [Dutch](../nl/README.md) | [Hebrew](../he/README.md) | [Vietnamese](./README.md) | [Indonesian](../id/README.md) | [Malay](../ms/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Swahili](../sw/README.md) | [Hungarian](../hu/README.md) | [Czech](../cs/README.md) | [Slovak](../sk/README.md) | [Romanian](../ro/README.md) | [Bulgarian](../bg/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Croatian](../hr/README.md) | [Slovenian](../sl/README.md) | [Ukrainian](../uk/README.md) | [Burmese (Myanmar)](../my/README.md)
**Nếu bạn muốn có thêm các ngôn ngữ dịch, danh sách các ngôn ngữ được hỗ trợ có [tại đây](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**Nếu bạn muốn có thêm các ngôn ngữ dịch, danh sách các ngôn ngữ được hỗ trợ có thể tìm thấy [ở đây](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## Tham gia cộng đồng
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## Bạn sẽ học được gì
## Những gì bạn sẽ học
**[Sơ đồ tư duy của khóa học](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
Trong chương trình học này, bạn sẽ học:
Trong chương trình này, bạn sẽ học:
* Các cách tiếp cận khác nhau đối với Trí tuệ Nhân tạo, bao gồm cách tiếp cận biểu tượng "cổ điển" với **Biểu diễn Kiến thức** và suy luận ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Mạng Nơ-ron** và **Học Sâu**, cốt lõi của AI hiện đại. Chúng tôi sẽ minh họa các khái niệm đằng sau những chủ đề quan trọng này bằng mã trong hai khung phổ biến nhất - [TensorFlow](http://Tensorflow.org) và [PyTorch](http://pytorch.org).
* **Kiến trúc Nơ-ron** để làm việc với hình ảnh và văn bản. Chúng tôi sẽ đề cập đến các mô hình gần đây nhưng có thể thiếu một chút về các mô hình tiên tiến nhất.
* Các cách tiếp cận AI ít phổ biến hơn, chẳng hạn như **Thuật toán Di truyền** và **Hệ thống Đa Tác nhân**.
* Các cách tiếp cận khác nhau đối với Trí tuệ nhân tạo, bao gồm cách tiếp cận biểu tượng "cổ điển" với **Biểu diễn tri thức** và suy luận ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
* **Mạng nơ-ron** và **Học sâu**, là cốt lõi của AI hiện đại. Chúng tôi sẽ minh họa các khái niệm đằng sau những chủ đề quan trọng này bằng mã trong hai framework phổ biến nhất - [TensorFlow](http://Tensorflow.org) và [PyTorch](http://pytorch.org).
* **Kiến trúc nơ-ron** để làm việc với hình ảnh và văn bản. Chúng tôi sẽ đề cập đến các mô hình gần đây nhưng có thể thiếu một chút về các mô hình tiên tiến nhất.
* Các cách tiếp cận AI ít phổ biến hơn, chẳng hạn như **Thuật toán di truyền** và **Hệ thống đa tác nhân**.
Những gì chúng tôi sẽ không đề cập trong chương trình học này:
Những gì chúng tôi sẽ không đề cập trong chương trình này:
> [Tìm tất cả các tài nguyên bổ sung cho khóa học này trong bộ sưu tập Microsoft Learn của chúng tôi](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* Các trường hợp sử dụng **AI trong Kinh doanh**. Hãy cân nhắc tham gia lộ trình học [Giới thiệu về AI cho người dùng kinh doanh](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) trên Microsoft Learn, hoặc [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), được phát triển cùng với [INSEAD](https://www.insead.edu/).
* **Học Máy Cổ điển**, được mô tả rất tốt trong [Chương trình Học Máy cho Người Mới Bắt Đầu](http://github.com/Microsoft/ML-for-Beginners).
* Các ứng dụng AI thực tế được xây dựng bằng **[Dịch vụ Nhận thức](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Để bắt đầu, chúng tôi khuyến nghị các mô-đun Microsoft Learn về [thị giác](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [xử lý ngôn ngữ tự nhiên](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[AI Tạo Sinh với Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** và các chủ đề khác.
* Các **Khung Đám mây ML** cụ thể, chẳng hạn như [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), hoặc [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Hãy cân nhắc sử dụng các lộ trình học [Xây dựng và vận hành giải pháp học máy với Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) và [Xây dựng và vận hành giải pháp học máy với Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI Đàm thoại** và **Chat Bots**. Có một lộ trình học riêng [Tạo giải pháp AI đàm thoại](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), và bạn cũng có thể tham khảo [bài viết blog này](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) để biết thêm chi tiết.
* **Toán học Sâu** đằng sau học sâu. Để tìm hiểu, chúng tôi khuyến nghị cuốn sách [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) của Ian Goodfellow, Yoshua Bengio và Aaron Courville, cũng có sẵn trực tuyến tại [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
* Các trường hợp sử dụng **AI trong kinh doanh**. Hãy cân nhắc tham gia lộ trình học [Giới thiệu về AI cho người dùng doanh nghiệp](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) trên Microsoft Learn, hoặc [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), được phát triển hợp tác với [INSEAD](https://www.insead.edu/).
* **Học máy cổ điển**, được mô tả rất tốt trong chương trình học [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners).
* Các ứng dụng AI thực tế được xây dựng bằng **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. Để bắt đầu, chúng tôi khuyến nghị các module Microsoft Learn về [thị giác](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [xử lý ngôn ngữ tự nhiên](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Generative AI với Azure OpenAI Service](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** và các module khác.
* Các framework **Cloud ML** cụ thể, chẳng hạn như [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum), [Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), hoặc [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum). Hãy cân nhắc sử dụng lộ trình học [Xây dựng và vận hành giải pháp học máy với Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) và [Xây dựng và vận hành giải pháp học máy với Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum).
* **AI hội thoại** và **Chat Bots**. Có một lộ trình học riêng [Tạo giải pháp AI hội thoại](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum), và bạn cũng có thể tham khảo [bài viết blog này](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) để biết thêm chi tiết.
* **Toán học sâu** đằng sau học sâu. Để tìm hiểu, chúng tôi khuyến nghị cuốn sách [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) của Ian Goodfellow, Yoshua Bengio và Aaron Courville, cũng có sẵn trực tuyến tại [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
Để có một cái nhìn tổng quan nhẹ nhàng về các chủ đề _AI trên Đám mây_, bạn có thể cân nhắc tham gia lộ trình học [Bắt đầu với trí tuệ nhân tạo trên Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
Để có một giới thiệu nhẹ nhàng về các chủ đề _AI trên Cloud_, bạn có thể cân nhắc tham gia lộ trình học [Bắt đầu với trí tuệ nhân tạo trên Azure](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum).
# Nội dung
| | Liên kết bài học | PyTorch/Keras/TensorFlow | Phòng thí nghiệm |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [Cài đặt khóa học](./lessons/0-course-setup/setup.md) | [Cài đặt môi trường phát triển của bạn](./lessons/0-course-setup/how-to-run.md) | |
| 0 | [Thiết lập khóa học](./lessons/0-course-setup/setup.md) | [Thiết lập môi trường phát triển của bạn](./lessons/0-course-setup/how-to-run.md) | |
| I | [**Giới thiệu về AI**](./lessons/1-Intro/README.md) | | |
| 01 | [Giới thiệu và Lịch sử AI](./lessons/1-Intro/README.md) | - | - |
| II | **AI Biểu tượng** |
| 02 | [Biểu diễn Kiến thức và Hệ chuyên gia](./lessons/2-Symbolic/README.md) | [Hệ chuyên gia](./lessons/2-Symbolic/Animals.ipynb) / [Ontology](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Đồ thị Khái niệm](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Giới thiệu về Mạng Nơ-ron**](./lessons/3-NeuralNetworks/README.md) |||
| 01 | [Giới thiệu và lịch sử AI](./lessons/1-Intro/README.md) | - | - |
| II | **AI biểu tượng** |
| 02 | [Biểu diễn tri thức và hệ thống chuyên gia](./lessons/2-Symbolic/README.md) | [Hệ thống chuyên gia](./lessons/2-Symbolic/Animals.ipynb) / [Ontology](./lessons/2-Symbolic/FamilyOntology.ipynb) /[Concept Graph](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**Giới thiệu về mạng nơ-ron**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [Perceptron](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [Phòng thí nghiệm](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [Perceptron Nhiều Lớp và Tạo khung của riêng chúng ta](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Phòng thí nghiệm](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 04 | [Perceptron nhiều lớp và tạo framework của riêng chúng ta](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [Phòng thí nghiệm](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [Giới thiệu về Frameworks (PyTorch/TensorFlow) và Overfitting](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**Thị giác máy tính**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Khám phá Thị giác Máy tính trên Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Giới thiệu về Thị giác Máy tính. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Mạng Nơ-ron Tích chập](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Kiến trúc CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Mạng được huấn luyện sẵn và Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) và [Các mẹo huấn luyện](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| IV | [**Thị giác máy tính**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [Khám phá Thị giác máy tính trên Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [Giới thiệu về Thị giác máy tính. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [Lab](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [Mạng Neural Tích chập](./lessons/4-ComputerVision/07-ConvNets/README.md) & [Kiến trúc CNN](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [Lab](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [Mạng đã được huấn luyện trước và Học chuyển tiếp](./lessons/4-ComputerVision/08-TransferLearning/README.md) và [Mẹo huấn luyện](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [Lab](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [Autoencoders và VAEs](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [Mạng Đối kháng Tạo sinh & Chuyển đổi Phong cách Nghệ thuật](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Phát hiện Đối tượng](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Phân đoạn Ngữ nghĩa. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Xử lý Ngôn ngữ Tự nhiên**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Khám phá Xử lý Ngôn ngữ Tự nhiên trên Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Biểu diễn Văn bản. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Embedding từ ngữ ngữ nghĩa. Word2Vec và GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Mô hình Ngôn ngữ. Huấn luyện embedding của riêng bạn](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Mạng Nơ-ron Hồi quy](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Mạng Hồi quy Tạo sinh](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Nhận diện Thực thể Được đặt tên](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Mô hình Ngôn ngữ Lớn, Lập trình Prompt và Nhiệm vụ Few-Shot](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Các Kỹ thuật AI Khác** || |
| 10 | [Mạng Đối kháng Sinh và Chuyển đổi Phong cách Nghệ thuật](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [Phát hiện đối tượng](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [Lab](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [Phân đoạn ngữ nghĩa. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**Xử lý ngôn ngữ tự nhiên**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [Khám phá Xử lý ngôn ngữ tự nhiên trên Microsoft Azure](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [Biểu diễn văn bản. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [Biểu diễn từ ngữ ngữ nghĩa. Word2Vec và GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [Mô hình ngôn ngữ. Huấn luyện biểu diễn của riêng bạn](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [Lab](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [Mạng Neural Hồi quy](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [Mạng Hồi quy Sinh](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [Lab](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [Nhận diện Thực thể Được đặt tên](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [Lab](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [Mô hình Ngôn ngữ Lớn, Lập trình Prompt và Nhiệm vụ Few-Shot](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **Các kỹ thuật AI khác** || |
| 21 | [Thuật toán Di truyền](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [Học Tăng cường Sâu](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [Lab](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [Hệ thống Đa Tác nhân](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **Đạo đức AI** | | |
| 24 | [Đạo đức AI và AI Có Trách nhiệm](./lessons/7-Ethics/README.md) | [Microsoft Learn: Nguyên tắc AI Có Trách nhiệm](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| 24 | [Đạo đức AI và AI có trách nhiệm](./lessons/7-Ethics/README.md) | [Microsoft Learn: Nguyên tắc AI có trách nhiệm](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **Phần bổ sung** | | |
| 25 | [Mạng Đa Phương thức, CLIP và VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| 25 | [Mạng Đa phương thức, CLIP và VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## Mỗi bài học bao gồm
* Tài liệu đọc trước
* Các Jupyter Notebook có thể thực thi, thường được thiết kế riêng cho từng framework (**PyTorch** hoặc **TensorFlow**). Notebook này cũng chứa nhiều tài liệu lý thuyết, vì vậy để hiểu chủ đề, bạn cần xem qua ít nhất một phiên bản của notebook (PyTorch hoặc TensorFlow).
* Các Jupyter Notebook có thể thực thi, thường được thiết kế riêng cho framework (**PyTorch** hoặc **TensorFlow**). Notebook thực thi cũng chứa nhiều tài liệu lý thuyết, vì vậy để hiểu chủ đề, bạn cần xem qua ít nhất một phiên bản của notebook (PyTorch hoặc TensorFlow).
* **Labs** có sẵn cho một số chủ đề, giúp bạn có cơ hội áp dụng kiến thức đã học vào một vấn đề cụ thể.
* Một số phần có liên kết đến các module [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) liên quan.
## Bắt đầu
- Chúng tôi đã tạo một [bài học thiết lập](./lessons/0-course-setup/setup.md) để giúp bạn thiết lập môi trường phát triển. - Đối với giáo viên, chúng tôi cũng đã tạo một [bài học thiết lập chương trình giảng dạy](./lessons/0-course-setup/for-teachers.md)!
- Chúng tôi đã tạo một [bài học thiết lập](./lessons/0-course-setup/setup.md) để giúp bạn thiết lập môi trường phát triển. - Đối với giáo viên, chúng tôi cũng đã tạo một [bài học thiết lập giáo trình](./lessons/0-course-setup/for-teachers.md)!
- Cách [Chạy mã trong VSCode hoặc Codepace](./lessons/0-course-setup/how-to-run.md)
Thực hiện các bước sau:
@ -121,31 +121,31 @@ Fork Repository: Nhấn vào nút "Fork" ở góc trên bên phải của trang
Clone Repository: `git clone https://github.com/microsoft/AI-For-Beginners.git`
Đừng quên gắn sao (🌟) repo này để dễ dàng tìm lại sau.
Đừng quên gắn sao (🌟) repo này để dễ tìm lại sau.
## Gặp gỡ các Học viên khác
## Gặp gỡ các học viên khác
Tham gia [máy chủ Discord AI chính thức](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) của chúng tôi để gặp gỡ và kết nối với các học viên khác đang tham gia khóa học này và nhận hỗ trợ.
Nếu bạn có phản hồi về sản phẩm hoặc câu hỏi trong khi xây dựng, hãy truy cập [Diễn đàn Nhà phát triển Azure AI Foundry](https://aka.ms/foundry/forum)
Nếu bạn có phản hồi về sản phẩm hoặc câu hỏi trong quá trình xây dựng, hãy truy cập [Diễn đàn Nhà phát triển Azure AI Foundry](https://aka.ms/foundry/forum)
## Câu hỏi trắc nghiệm
> **Lưu ý về các bài kiểm tra**: Tất cả các bài kiểm tra được lưu trong thư mục Quiz-app tại etc\quiz-app, hoặc [Trực tuyến tại đây](https://ff-quizzes.netlify.app/). Chúng được liên kết từ trong các bài học. Ứng dụng kiểm tra có thể được chạy cục bộ hoặc triển khai lên Azure; hãy làm theo hướng dẫn trong thư mục `quiz-app`. Các bài kiểm tra đang dần được bản địa hóa.
## Cần Trợ Giúp
## Câu hỏi kiểm tra
> **Lưu ý về các bài kiểm tra**: Tất cả các bài kiểm tra được lưu trong thư mục Quiz-app tại etc\quiz-app, hoặc [Trực tuyến tại đây](https://ff-quizzes.netlify.app/). Chúng được liên kết từ trong các bài học. Ứng dụng kiểm tra có thể chạy cục bộ hoặc triển khai lên Azure; hãy làm theo hướng dẫn trong thư mục `quiz-app`. Các bài kiểm tra đang dần được bản địa hóa.
## Cần Giúp Đỡ
Bạn có đề xuất hoặc phát hiện lỗi chính tả hay lỗi mã? Hãy tạo một issue hoặc gửi một pull request.
Bạn có đề xuất hoặc phát hiện lỗi chính tả hay lỗi mã? Hãy tạo một vấn đề hoặc gửi yêu cầu kéo.
## Lời Cảm Ơn Đặc Biệt
## Cảm Ơn Đặc Biệt
* **✍️ Tác giả chính:** [Dmitry Soshnikov](http://soshnikov.com), Tiến sĩ
* **🔥 Biên tập viên:** [Jen Looper](https://twitter.com/jenlooper), Tiến sĩ
* **🎨 Minh họa Sketchnote:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ Người tạo câu đố:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **✅ Người tạo câu hỏi:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 Những người đóng góp chính:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## Các Chương Trình Học Khác
Nhóm của chúng tôi còn sản xuất các chương trình học khác! Hãy xem qua:
Nhóm của chúng tôi sản xuất các chương trình học khác! Hãy xem:
- [Generative AI for Beginners](https://aka.ms/genai-beginners)
- [Generative AI for Beginners .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)

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@ -1,8 +1,8 @@
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[![](https://dcbadge.vercel.app/api/server/ByRwuEEgH4)](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott)
# 人工智能入门 - 一套课程
# 人工智能入门课程 - 学习计划
|![由 @girlie_mac 绘制的草图笔记 https://twitter.com/girlie_mac](../../lessons/sketchnotes/ai-overview.png)|
|:---:|
| 人工智能入门 - _草图笔记由 [@girlie_mac](https://twitter.com/girlie_mac) 绘制_ |
|![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](../../translated_images/ai-overview.0857791951d19500d0ef8b803d77110c738dcafc52306e6d68724742cd4af167.zh.png)|
|:---:|
| 人工智能入门 - _由 [@girlie_mac](https://twitter.com/girlie_mac) 绘制的速写笔记_ |
通过我们的 12 周、24 节课程，探索**人工智能**（AI）的世界！课程包括实践课程、测验和实验室，适合初学者，涵盖了 TensorFlow 和 PyTorch 等工具，以及 AI 的伦理问题。
通过我们的 12 周、24 节课程学习计划，探索**人工智能**（AI）的世界！课程包括实践课程、测验和实验室。该课程面向初学者，涵盖了 TensorFlow 和 PyTorch 等工具，以及人工智能伦理相关内容。
### 🌐 多语言支持
### 🌐 多语言支持
#### 通过 GitHub Action 支持（自动化且始终保持最新）
#### 通过 GitHub Action 支持（自动更新，始终保持最新）
[法语](../fr/README.md) | [西班牙语](../es/README.md) | [德语](../de/README.md) | [俄语](../ru/README.md) | [阿拉伯语](../ar/README.md) | [波斯语（法尔西语）](../fa/README.md) | [乌尔都语](../ur/README.md) | [中文（简体）](./README.md) | [中文（繁体，澳门）](../mo/README.md) | [中文（繁体，香港）](../hk/README.md) | [中文（繁体，台湾）](../tw/README.md) | [日语](../ja/README.md) | [韩语](../ko/README.md) | [印地语](../hi/README.md) | [孟加拉语](../bn/README.md) | [马拉地语](../mr/README.md) | [尼泊尔语](../ne/README.md) | [旁遮普语（古尔穆基文）](../pa/README.md) | [葡萄牙语（葡萄牙）](../pt/README.md) | [葡萄牙语（巴西）](../br/README.md) | [意大利语](../it/README.md) | [波兰语](../pl/README.md) | [土耳其语](../tr/README.md) | [希腊语](../el/README.md) | [泰语](../th/README.md) | [瑞典语](../sv/README.md) | [丹麦语](../da/README.md) | [挪威语](../no/README.md) | [芬兰语](../fi/README.md) | [荷兰语](../nl/README.md) | [希伯来语](../he/README.md) | [越南语](../vi/README.md) | [印尼语](../id/README.md) | [马来语](../ms/README.md) | [他加禄语（菲律宾语）](../tl/README.md) | [斯瓦希里语](../sw/README.md) | [匈牙利语](../hu/README.md) | [捷克语](../cs/README.md) | [斯洛伐克语](../sk/README.md) | [罗马尼亚语](../ro/README.md) | [保加利亚语](../bg/README.md) | [塞尔维亚语（西里尔文）](../sr/README.md) | [克罗地亚语](../hr/README.md) | [斯洛文尼亚语](../sl/README.md) | [乌克兰语](../uk/README.md) | [缅甸语（缅甸）](../my/README.md)
[法语](../fr/README.md) | [西班牙语](../es/README.md) | [德语](../de/README.md) | [俄语](../ru/README.md) | [阿拉伯语](../ar/README.md) | [波斯语（法尔西语）](../fa/README.md) | [乌尔都语](../ur/README.md) | [中文（简体）](./README.md) | [中文（繁体，澳门）](../mo/README.md) | [中文（繁体，香港）](../hk/README.md) | [中文（繁体，台湾）](../tw/README.md) | [日语](../ja/README.md) | [韩语](../ko/README.md) | [印地语](../hi/README.md) | [孟加拉语](../bn/README.md) | [马拉地语](../mr/README.md) | [尼泊尔语](../ne/README.md) | [旁遮普语（古木基文）](../pa/README.md) | [葡萄牙语（葡萄牙）](../pt/README.md) | [葡萄牙语（巴西）](../br/README.md) | [意大利语](../it/README.md) | [波兰语](../pl/README.md) | [土耳其语](../tr/README.md) | [希腊语](../el/README.md) | [泰语](../th/README.md) | [瑞典语](../sv/README.md) | [丹麦语](../da/README.md) | [挪威语](../no/README.md) | [芬兰语](../fi/README.md) | [荷兰语](../nl/README.md) | [希伯来语](../he/README.md) | [越南语](../vi/README.md) | [印尼语](../id/README.md) | [马来语](../ms/README.md) | [他加禄语（菲律宾语）](../tl/README.md) | [斯瓦希里语](../sw/README.md) | [匈牙利语](../hu/README.md) | [捷克语](../cs/README.md) | [斯洛伐克语](../sk/README.md) | [罗马尼亚语](../ro/README.md) | [保加利亚语](../bg/README.md) | [塞尔维亚语（西里尔文）](../sr/README.md) | [克罗地亚语](../hr/README.md) | [斯洛文尼亚语](../sl/README.md) | [乌克兰语](../uk/README.md) | [缅甸语（缅甸）](../my/README.md)
**如果您希望支持其他语言，支持的语言列表请参考[这里](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
**如果您希望支持其他语言，支持的语言列表请参见 [此处](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
## 加入社区
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## 加入社区
[![Azure AI Discord](https://dcbadge.limes.pink/api/server/kzRShWzttr)](https://discord.gg/kzRShWzttr)
## 您将学到什么
## 您将学到什么
**[课程思维导图](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
**[课程思维导图](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
在本课程中，您将学习：
在本课程中，您将学习：
* 人工智能的不同方法，包括“经典”的符号方法，即通过**知识表示**和推理（[GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)）。
* **神经网络**和**深度学习**，它们是现代 AI 的核心。我们将通过两种最流行的框架 [TensorFlow](http://Tensorflow.org) 和 [PyTorch](http://pytorch.org) 的代码来说明这些重要主题背后的概念。
* 用于处理图像和文本的**神经架构**。我们将涵盖一些近期模型，但可能不包括最前沿的内容。
* 不太流行的 AI 方法，例如**遗传算法**和**多智能体系统**。
* 人工智能的不同方法，包括“经典”的符号方法，如**知识表示**和推理（[GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)）。
* **神经网络**和**深度学习**，它们是现代人工智能的核心。我们将使用两个最流行的框架——[TensorFlow](http://Tensorflow.org) 和 [PyTorch](http://pytorch.org) 的代码来说明这些重要主题背后的概念。
* 用于处理图像和文本的**神经网络架构**。我们将涵盖一些最新模型，但可能不包括最前沿的技术。
* 不太流行的人工智能方法，例如**遗传算法**和**多智能体系统**。
本课程不包括以下内容：
本课程不包括以下内容：
> [在我们的 Microsoft Learn 集合中找到本课程的所有附加资源](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
> [在我们的 Microsoft Learn 集合中找到本课程的所有额外资源](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
* **AI 在商业中的应用案例**。建议学习 Microsoft Learn 上的 [面向商业用户的 AI 入门](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum)学习路径，或与 [INSEAD](https://www.insead.edu/) 合作开发的 [AI 商学院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)。
* **经典机器学习**，这在我们的[机器学习入门课程](http://github.com/Microsoft/ML-for-Beginners)中有详细描述。
* 使用 **[认知服务](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** 构建的实际 AI 应用。建议从 Microsoft Learn 的模块开始学习，例如[视觉](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然语言处理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[Azure OpenAI 服务的生成式 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)**等。
* 特定的 ML **云框架**，如 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) 或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。建议学习 [使用 Azure Machine Learning 构建和操作机器学习解决方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 和 [使用 Azure Databricks 构建和操作机器学习解决方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 学习路径。
* **对话式 AI** 和 **聊天机器人**。可以参考单独的 [创建对话式 AI 解决方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum)学习路径，或者参考[这篇博客文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)了解更多细节。
* **深度学习的数学原理**。建议阅读 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 的 [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)，该书也可在线获取：[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
* **人工智能在商业中的应用案例**。建议学习 Microsoft Learn 上的 [面向商业用户的人工智能简介](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 学习路径，或与 [INSEAD](https://www.insead.edu/) 合作开发的 [AI 商业学院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)。
* **经典机器学习**，这在我们的 [机器学习入门课程](http://github.com/Microsoft/ML-for-Beginners) 中有详细描述。
* 使用 **[认知服务](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** 构建的实际人工智能应用。建议从 Microsoft Learn 的模块开始学习 [视觉](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然语言处理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[Azure OpenAI 服务的生成式人工智能](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 等内容。
* 特定的机器学习**云框架**，例如 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) 或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。建议学习 [使用 Azure Machine Learning 构建和操作机器学习解决方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 和 [使用 Azure Databricks 构建和操作机器学习解决方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 学习路径。
* **对话式人工智能**和**聊天机器人**。有一个单独的 [创建对话式人工智能解决方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) 学习路径，您也可以参考 [这篇博客文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) 了解更多细节。
* **深度学习背后的数学原理**。建议阅读 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 的 [深度学习](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)，该书也可在线访问：[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。
如果您想了解 _云中的 AI_ 的入门知识，可以学习 [在 Azure 上开始人工智能](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum)学习路径。
如果您希望对 _云中的人工智能_ 主题有一个温和的介绍，可以考虑学习 [在 Azure 上开始人工智能](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 学习路径。
# 内容
# 内容
| | 课程链接 | PyTorch/Keras/TensorFlow | 实验室 |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [课程设置](./lessons/0-course-setup/setup.md) | [设置开发环境](./lessons/0-course-setup/how-to-run.md) | |
| I | [**AI 简介**](./lessons/1-Intro/README.md) | | |
| 01 | [AI 的简介与历史](./lessons/1-Intro/README.md) | - | - |
| II | **符号 AI** |
| 02 | [知识表示与专家系统](./lessons/2-Symbolic/README.md) | [专家系统](./lessons/2-Symbolic/Animals.ipynb) / [本体](./lessons/2-Symbolic/FamilyOntology.ipynb) /[概念图](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**神经网络简介**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [感知器](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [实验室](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [多层感知器与创建我们自己的框架](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [实验室](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [框架入门（PyTorch/TensorFlow）和过拟合](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [实验](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**计算机视觉**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [在 Microsoft Azure 上探索计算机视觉](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [计算机视觉入门. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [实验](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| | 课程链接 | PyTorch/Keras/TensorFlow | 实验室 |
| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
| 0 | [课程设置](./lessons/0-course-setup/setup.md) | [设置开发环境](./lessons/0-course-setup/how-to-run.md) | |
| I | [**人工智能简介**](./lessons/1-Intro/README.md) | | |
| 01 | [人工智能的介绍与历史](./lessons/1-Intro/README.md) | - | - |
| II | **符号人工智能** |
| 02 | [知识表示与专家系统](./lessons/2-Symbolic/README.md) | [专家系统](./lessons/2-Symbolic/Animals.ipynb) / [本体论](./lessons/2-Symbolic/FamilyOntology.ipynb) /[概念图](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
| III | [**神经网络简介**](./lessons/3-NeuralNetworks/README.md) |||
| 03 | [感知器](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [笔记本](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [实验室](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) |
| 04 | [多层感知器与创建我们自己的框架](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [笔记本](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [实验室](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) |
| 05 | [框架介绍（PyTorch/TensorFlow）和过拟合](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [实验](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
| IV | [**计算机视觉**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [探索 Microsoft Azure 上的计算机视觉](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
| 06 | [计算机视觉介绍. OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [笔记本](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [实验](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
| 07 | [卷积神经网络](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN 架构](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [实验](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) |
| 08 | [预训练网络和迁移学习](./lessons/4-ComputerVision/08-TransferLearning/README.md) 和 [训练技巧](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [实验](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) |
| 09 | [自编码器和变分自编码器 (VAEs)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 09 | [自动编码器和变分自动编码器 (VAEs)](./lessons/4-ComputerVision/09-Autoencoders/README.md) | [PyTorch](./lessons/4-ComputerVision/09-Autoencoders/AutoEncodersPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/09-Autoencoders/AutoencodersTF.ipynb) | |
| 10 | [生成对抗网络 (GANs) 和艺术风格迁移](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | |
| 11 | [目标检测](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [实验](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) |
| 12 | [语义分割. U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
| V | [**自然语言处理**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [在 Microsoft Azure 上探索自然语言处理](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [文本表示. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](./lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [语义词嵌入. Word2Vec 和 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](./lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [语言建模. 训练自己的词嵌入](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](./lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [实验](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [循环神经网络 (RNN)](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](./lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](./lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成型循环网络](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](./lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.md) / [TensorFlow](./lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.md) | [实验](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformers. BERT.](./lessons/5-NLP/18-Transformers/READMEtransformers.md) | [PyTorch](./lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](./lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [命名实体识别 (NER)](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](./lessons/5-NLP/19-NER/NER-TF.ipynb) | [实验](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大型语言模型、提示编程和少样本任务](./lessons/5-NLP/20-LangModels/READMELargeLang.md) | [PyTorch](./lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| V | [**自然语言处理**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [探索 Microsoft Azure 上的自然语言处理](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
| 13 | [文本表示. Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | |
| 14 | [语义词嵌入. Word2Vec 和 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | |
| 15 | [语言建模. 训练自己的嵌入](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [实验](./lessons/5-NLP/15-LanguageModeling/lab/README.md) |
| 16 | [循环神经网络 (RNN)](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
| 17 | [生成式循环网络](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [实验](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
| 18 | [Transformer. BERT.](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | |
| 19 | [命名实体识别 (NER)](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [实验](./lessons/5-NLP/19-NER/lab/README.md) |
| 20 | [大型语言模型、提示编程和少样本任务](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
| VI | **其他 AI 技术** || |
| 21 | [遗传算法](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 21 | [遗传算法](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [笔记本](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
| 22 | [深度强化学习](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [实验](./lessons/6-Other/22-DeepRL/lab/README.md) |
| 23 | [多智能体系统](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
| VII | **AI 伦理** | | |
| 24 | [AI 伦理与负责任的 AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: 负责任的 AI 原则](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **附加内容** | | |
| 25 | [多模态网络, CLIP 和 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
| VII | **AI伦理** | | |
| 24 | [AI伦理与负责任的AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: 负责任的AI原则](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
| IX | **额外内容** | | |
| 25 | [多模态网络、CLIP 和 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [笔记本](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
## 每节课包含
* 预读材料
* 可执行的 Jupyter Notebooks，通常针对特定框架（**PyTorch** 或 **TensorFlow**）。这些可执行的 Notebook 还包含大量理论内容，因此要理解主题，至少需要学习一个版本的 Notebook（PyTorch 或 TensorFlow）。
* **实验**（部分主题提供），让你有机会将所学内容应用到具体问题中。
* 部分章节包含指向 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模块的链接，这些模块涵盖相关主题。
* 预读材料
* 可执行的 Jupyter 笔记本，通常针对特定框架（**PyTorch** 或 **TensorFlow**）。可执行笔记本还包含大量理论内容，因此要理解主题，至少需要学习一个版本的笔记本（PyTorch 或 TensorFlow）。
* **实验**：部分主题提供实验机会，让你尝试将所学知识应用于具体问题。
* 部分章节包含链接到 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模块，涵盖相关主题。
## 入门指南
## 开始学习
- 我们创建了一个 [设置课程](./lessons/0-course-setup/setup.md) 来帮助你设置开发环境。
- 对于教育工作者，我们还创建了一个 [课程设置指南](./lessons/0-course-setup/for-teachers.md)！
- 如何[在 VSCode 或 CodeSpace 中运行代码](./lessons/0-course-setup/how-to-run.md)
- 我们创建了一个 [设置课程](./lessons/0-course-setup/setup.md) 来帮助你设置开发环境。
- 对于教育工作者，我们还创建了一个 [课程设置指南](./lessons/0-course-setup/for-teachers.md)。
- 如何 [在 VSCode 或 Codepace 中运行代码](./lessons/0-course-setup/how-to-run.md)。
按照以下步骤操作：
1. Fork 仓库：点击页面右上角的 "Fork" 按钮。
2. 克隆仓库：`git clone https://github.com/microsoft/AI-For-Beginners.git`
3. 别忘了给这个仓库加星标（🌟），方便以后找到。
1. Fork 仓库：点击页面右上角的 "Fork" 按钮。
2. 克隆仓库：`git clone https://github.com/microsoft/AI-For-Beginners.git`
3. 别忘了给这个仓库加星标 (🌟)，方便以后找到。
## 认识其他学习者
## 结识其他学习者
加入我们的 [官方 AI Discord 服务器](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)，与其他学习者交流并获得支持。
@ -136,32 +136,32 @@ CO_OP_TRANSLATOR_METADATA:
## 特别感谢
* **✍️ 主要作者：** [Dmitry Soshnikov](http://soshnikov.com)，博士
* **🔥 编辑：** [Jen Looper](https://twitter.com/jenlooper)，博士
* **🎨 手绘笔记插画师：** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ 测验创建者：** [Lateefah Bello](https://github.com/CinnamonXI)，[MLSA](https://studentambassadors.microsoft.com/)
* **🙏 核心贡献者：** [Evgenii Pishchik](https://github.com/Pe4enIks)
* **✍️ 主要作者:** [Dmitry Soshnikov](http://soshnikov.com), 博士
* **🔥 编辑:** [Jen Looper](https://twitter.com/jenlooper), 博士
* **🎨 手绘笔记插画师:** [Tomomi Imura](https://twitter.com/girlie_mac)
* **✅ 测验创建者:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
* **🙏 核心贡献者:** [Evgenii Pishchik](https://github.com/Pe4enIks)
## 其他课程
我们的团队还制作了其他课程！请查看：
我们的团队还制作了其他课程！请查看以下内容：
- [生成式 AI 初学者课程](https://aka.ms/genai-beginners)
- [生成式 AI 初学者课程 .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [初学者生成式 AI](https://aka.ms/genai-beginners)
- [初学者生成式 AI .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet)
- [使用 JavaScript 的生成式 AI](https://github.com/microsoft/generative-ai-with-javascript)
- [使用 Java 的生成式 AI](https://github.com/microsoft/Generative-AI-for-beginners-java)
- [AI 初学者课程](https://aka.ms/ai-beginners)
- [数据科学初学者课程](https://aka.ms/datascience-beginners)
- [机器学习初学者课程](https://aka.ms/ml-beginners)
- [网络安全初学者课程](https://github.com/microsoft/Security-101)
- [Web 开发初学者课程](https://aka.ms/webdev-beginners)
- [物联网初学者课程](https://aka.ms/iot-beginners)
- [XR 开发初学者课程](https://github.com/microsoft/xr-development-for-beginners)
- [初学者 AI](https://aka.ms/ai-beginners)
- [初学者数据科学](https://aka.ms/datascience-beginners)
- [初学者机器学习](https://aka.ms/ml-beginners)
- [初学者网络安全](https://github.com/microsoft/Security-101)
- [初学者 Web 开发](https://aka.ms/webdev-beginners)
- [初学者物联网](https://aka.ms/iot-beginners)
- [初学者 XR 开发](https://github.com/microsoft/xr-development-for-beginners)
- [掌握 GitHub Copilot 的智能使用](https://github.com/microsoft/Mastering-GitHub-Copilot-for-Paired-Programming)
- [掌握 GitHub Copilot 的 C#/.NET 开发者课程](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [为 C#/.NET 开发者掌握 GitHub Copilot](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers)
- [选择你的 Copilot 冒险之旅](https://github.com/microsoft/CopilotAdventures)
---
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本文档使用AI翻译服务[Co-op Translator](https://github.com/Azure/co-op-translator)进行翻译。尽管我们努力确保翻译的准确性，但请注意，自动翻译可能包含错误或不准确之处。原始语言的文档应被视为权威来源。对于关键信息，建议使用专业人工翻译。我们对因使用此翻译而产生的任何误解或误读不承担责任。
本文档使用AI翻译服务[Co-op Translator](https://github.com/Azure/co-op-translator)进行翻译。尽管我们努力确保准确性，但请注意，自动翻译可能包含错误或不准确之处。应以原始语言的文档作为权威来源。对于关键信息，建议使用专业人工翻译。因使用本翻译而导致的任何误解或误读，我们概不负责。