[](https://github.com/microsoft/AI-For-Beginners/blob/main/LICENSE) [](https://GitHub.com/microsoft/AI-For-Beginners/graphs/contributors/) [](https://GitHub.com/microsoft/AI-For-Beginners/issues/) [](https://GitHub.com/microsoft/AI-For-Beginners/pulls/) [](http://makeapullrequest.com) [](https://GitHub.com/microsoft/AI-For-Beginners/watchers/) [](https://GitHub.com/microsoft/AI-For-Beginners/network/) [](https://GitHub.com/microsoft/AI-For-Beginners/stargazers/) [](https://mybinder.org/v2/gh/microsoft/ai-for-beginners/HEAD) [](https://gitter.im/Microsoft/ai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) [](https://discord.gg/zxKYvhSnVp?WT.mc_id=academic-000002-leestott) # Kunstig intelligens for begyndere - Et pensum || |:---:| | AI For Beginners - _Sketchnote af [@girlie_mac](https://twitter.com/girlie_mac)_ | Udforsk verdenen af **Kunstig intelligens** (AI) med vores 12-ugers pensum, der består af 24 lektioner! Det inkluderer praktiske lektioner, quizzer og laboratorier. Pensummet er venligt for begyndere og dækker værktøjer som TensorFlow og PyTorch samt etik inden for AI. ### 🌐 Understøttelse af flere sprog #### Understøttet via GitHub Action (Automatisk & 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) **Hvis du ønsker yderligere oversættelser, er understøttede sprog listet [her](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)** ## Bliv en del af fællesskabet [](https://discord.gg/kzRShWzttr) ## Hvad du vil lære **[Mindmap af kurset](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** I dette pensum 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 kan mangle lidt i forhold til det nyeste. * Mindre populære AI-tilgange, såsom **Genetiske algoritmer** og **Multi-Agent Systems**. Hvad vi ikke vil dække i dette pensum: > [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) * Forretningscases for brug 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) læringssti 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 [Machine Learning for Beginners Curriculum](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 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 [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) og [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) læringsstier. * **Konversations-AI** og **Chat Bots**. Der er en separat [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) læringssti, og du kan også referere til [denne blogpost](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) for mere detaljer. * **Dybtgående 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) læringssti. # Indhold | | Lektion Link | PyTorch/Keras/TensorFlow | Lab | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 0 | [Kursusopsætning](./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) | | 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) | | 07 | [Convolutional Neural Networks](./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 | [Forudtrænede Netværk og Transfer Learning](./lessons/4-ComputerVision/08-TransferLearning/README.md) og [Træningstips](./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 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) | | | 10 | [Generative Adversarial Networks & Kunstnerisk Stiloverførsel](./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 | [**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 | [Sproglig Modellering. 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) | | | 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) | | 23 | [Multi-Agent Systemer](./lessons/6-Other/23-MultiagentSystems/README.md) | | | | VII | **AI Etik** | | | | 24 | [AI Etik og Ansvarlig AI](./lessons/7-Ethics/README.md) | [Microsoft Learn: Ansvarlige AI-principper](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | | | IX | **Ekstra** | | | | 25 | [Multi-Modal Netværk, CLIP og VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | | ## Hver lektion indeholder * Forberedende læsemateriale * Eksekverbare Jupyter Notebooks, som ofte er specifikke for frameworket (**PyTorch** eller **TensorFlow**). Den eksekverbare notebook indeholder også en masse teoretisk materiale, så for at forstå emnet skal du gennemgå mindst én version af notebooken (enten PyTorch eller TensorFlow). * **Labs** tilgængelige for nogle emner, som giver dig mulighed for at prøve at anvende det materiale, du har lært, på et specifikt problem. * Nogle sektioner indeholder links til [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) moduler, der dækker relaterede emner. ## Kom godt i gang - Vi har oprettet en [opsætningslektion](./lessons/0-course-setup/setup.md) for at hjælpe dig med at opsætte dit udviklingsmiljø. - For undervisere har vi også oprettet en [curricula opsætningslektion](./lessons/0-course-setup/for-teachers.md)! - Sådan [kører du koden i VSCode eller en Codespace](./lessons/0-course-setup/how-to-run.md) Følg disse trin: Fork repositoryet: Klik på "Fork"-knappen øverst til højre på denne side. Klon repositoryet: `git clone https://github.com/microsoft/AI-For-Beginners.git` Glem ikke at stjerne (🌟) dette repo for nemmere at finde det senere. ## Mød andre lærende Deltag i vores [officielle AI Discord-server](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) for at møde og netværke med andre lærende, der tager dette kursus, og få support. Hvis du har produktfeedback eller spørgsmål undervejs, kan du besøge vores [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) ## Quizzer > **En note om quizzer**: Alle quizzer findes i Quiz-app-mappen i etc\quiz-app, eller [Online Her](https://ff-quizzes.netlify.app/) De er linket fra lektionerne, og quiz-appen kan køres lokalt eller implementeres på Azure; følg instruktionerne i `quiz-app`-mappen. De bliver gradvist lokaliseret. ## Hjælp ønskes Har du forslag eller fundet stave- eller kodefejl? Opret en issue eller lav en pull request. ## Særlig tak * **✍️ Primær forfatter:** [Dmitry Soshnikov](http://soshnikov.com), PhD * **🔥 Redaktør:** [Jen Looper](https://twitter.com/jenlooper), PhD * **🎨 Sketchnote illustrator:** [Tomomi Imura](https://twitter.com/girlie_mac) * **✅ Quiz-skaber:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/) * **🙏 Kernebidragydere:** [Evgenii Pishchik](https://github.com/Pe4enIks) ## Andre læseplaner Vores team producerer andre læseplaner! Tjek dem ud: - [Generativ AI for begyndere](https://aka.ms/genai-beginners) - [Generativ AI for begyndere .NET](https://github.com/microsoft/Generative-AI-for-beginners-dotnet) - [Generativ AI med JavaScript](https://github.com/microsoft/generative-ai-with-javascript) - [Generativ AI med Java](https://github.com/microsoft/Generative-AI-for-beginners-java) - [AI for begyndere](https://aka.ms/ai-beginners) - [Data Science for begyndere](https://aka.ms/datascience-beginners) - [ML for begyndere](https://aka.ms/ml-beginners) - [Cybersikkerhed for begyndere](https://github.com/microsoft/Security-101) - [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) - [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 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.