From d22ccfbffb961099cd427e83455133925edbeb50 Mon Sep 17 00:00:00 2001 From: "localizeflow[bot]" Date: Sat, 28 Feb 2026 10:00:44 +0000 Subject: [PATCH] chore(i18n): sync translations with latest source changes (chunk 1/1, 9 changes) --- translations/bn/.co-op-translator.json | 10 +- translations/bn/README.md | 178 +-- .../lessons/2-Symbolic/MSConceptGraph.ipynb | 1065 ++++++++--------- translations/hi/.co-op-translator.json | 10 +- translations/hi/README.md | 194 +-- .../lessons/2-Symbolic/MSConceptGraph.ipynb | 1064 ++++++++-------- translations/ko/.co-op-translator.json | 10 +- translations/ko/README.md | 176 +-- .../lessons/2-Symbolic/MSConceptGraph.ipynb | 1065 ++++++++--------- 9 files changed, 1898 insertions(+), 1874 deletions(-) diff --git a/translations/bn/.co-op-translator.json b/translations/bn/.co-op-translator.json index 42563621..a1056872 100644 --- a/translations/bn/.co-op-translator.json +++ b/translations/bn/.co-op-translator.json @@ -6,8 +6,8 @@ "language_code": "bn" }, "README.md": { - "original_hash": "75fe3383afc51eaa84b82ace619ffea7", - "translation_date": "2026-02-06T07:50:23+00:00", + "original_hash": "9eaca839b0b3f6d7f0a195fd33cebd30", + "translation_date": "2026-02-28T10:00:36+00:00", "source_file": "README.md", "language_code": "bn" }, @@ -89,6 +89,12 @@ "source_file": "lessons/1-Intro/assignment.md", "language_code": "bn" }, + "lessons/2-Symbolic/MSConceptGraph.ipynb": { + "original_hash": "e5690bbc6e5119a96a8172ec7261db67", + "translation_date": "2026-02-28T09:56:22+00:00", + "source_file": "lessons/2-Symbolic/MSConceptGraph.ipynb", + "language_code": "bn" + }, "lessons/2-Symbolic/README.md": { "original_hash": "f9f06b266b8b2bfc6b8792ff2bb1bea4", "translation_date": "2026-01-15T13:05:39+00:00", diff --git a/translations/bn/README.md b/translations/bn/README.md index db9088d2..fad22a14 100644 --- a/translations/bn/README.md +++ b/translations/bn/README.md @@ -12,159 +12,167 @@ [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -# নবীনদের জন্য কৃত্রিম বুদ্ধিমত্তা - একটি পাঠ্যক্রম +# কৃত্রিম বুদ্ধিমত্তার জন্য শিক্ষানবীষ - একটি পাঠ্যক্রম |![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](https://github.com/microsoft/AI-For-Beginners/raw/main/lessons/sketchnotes/ai-overview.png)| |:---:| -| নবীনদের জন্য AI - _স্কেচনোট [@girlie_mac](https://twitter.com/girlie_mac) এর দ্বারা_ | +| শিখননবীষদের জন্য AI - _স্কেচনোট [@girlie_mac](https://twitter.com/girlie_mac) দ্বারা_ | -আমাদের ১২ সপ্তাহের, ২৪টি পাঠের পাঠ্যক্রমের মাধ্যমে **কৃত্রিম বুদ্ধিমত্তা** (AI) এর জগৎ অন্বেষণ করুন! এতে ব্যবহারিক পাঠ, কুইজ এবং ল্যাব অন্তর্ভুক্ত রয়েছে। পাঠ্যক্রমটি নবীনদের জন্য বানানো হয়েছে এবং এতে TensorFlow ও PyTorch এর মতো টুল এবং AI-তে নৈতিকতা অন্তর্ভুক্ত রয়েছে। +আমাদের ১২ সপ্তাহ, ২৪টি পাঠের পাঠ্যক্রমের সাথে **কৃত্রিম বুদ্ধিমত্তার** (AI) জগৎ অন্বেষণ করুন! এতে রয়েছে ব্যবহারিক পাঠ, কুইজ, এবং ল্যাব। এই পাঠ্যক্রমটি শিক্ষানবীষদের জন্য-friendly এবং এতে TensorFlow এবং PyTorch এর মতো টুলসসহ AI-তে নীতিশাস্ত্রও অন্তর্ভুক্ত রয়েছে। ### 🌐 বহুভাষী সমর্থন -#### GitHub Action এর মাধ্যমে সমর্থিত (স্বয়ংক্রিয় এবং সর্বদা হালনাগাদ) +#### GitHub Action এর মাধ্যমে সমর্থিত (স্বয়ঞ্চালিত এবং সর্বদা আপ-টু-ডেট) [Arabic](../ar/README.md) | [Bengali](./README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](../zh-HK/README.md) | [Chinese (Traditional, Macau)](../zh-MO/README.md) | [Chinese (Traditional, Taiwan)](../zh-TW/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../pt-BR/README.md) | [Portuguese (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) -> **স্থানীয়ভাবে ক্লোন করতে ইচ্ছুক?** - -> এই রিপোজিটরিতে ৫০+ ভাষার অনুবাদ অন্তর্ভুক্ত রয়েছে যা ডাউনলোড সাইজ অনেক বৃদ্ধি করে। অনুবাদ ছাড়া ক্লোন করতে স্পার্স চেকআউট ব্যবহার করুন: +> **স্থানীয়ভাবে ক্লোন করতে চান?** +> +> এই রিপোজিটরিতে ৫০+ ভাষার অনুবাদ রয়েছে যা ডাউনলোড সাইজ ব্যাপকভাবে বাড়ায়। অনুবাদ ছাড়া ক্লোন করতে, sparse checkout ব্যবহার করুন: +> +> **বাশ / macOS / Linux:** > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git > cd AI-For-Beginners > git sparse-checkout set --no-cone '/*' '!translations' '!translated_images' > ``` -> এটি আপনাকে কোর্স সম্পন্ন করার জন্য যা কিছু প্রয়োজন তা দ্রুত ডাউনলোডে দেবে। +> +> **CMD (Windows):** +> ```cmd +> git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git +> cd AI-For-Beginners +> git sparse-checkout set --no-cone "/*" "!translations" "!translated_images" +> ``` +> +> এই ভাবে আপনি কোর্স সম্পন্ন করার জন্য যা যা দরকার তা অনেক দ্রুত ডাউনলোড করতে পাবেন। -**আপনি যদি অতিরিক্ত অনুবাদ ভাষা চান, সেগুলি এখানে তালিকাভুক্ত আছে [এখানে](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)** +**অতিরিক্ত অনুবাদের জন্য, আপনি চাইলে সমর্থিত ভাষাগুলোর তালিকা [এখানে](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) দেখতে পারেন।** ## কমিউনিটিতে যোগ দিন [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -## আপনি কি শিখবেন +## আপনি কী শিখবেন **[কোর্সের মাইন্ডম্যাপ](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** এই পাঠ্যক্রমে আপনি শিখবেন: -* কৃত্রিম বুদ্ধিমত্তার বিভিন্ন পদ্ধতি, যার মধ্যে "পরিচিত পুরনো" প্রতীকী পদ্ধতি যেমন **জ্ঞান উপস্থাপনা** এবং যুক্তি প্রয়োগ ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)) অন্তর্ভুক্ত। -* **নিউরাল নেটওয়ার্কস** এবং **ডীপ লার্নিং**, যা আধুনিক AI এর মূল ভিত্তি। এই গুরুত্বপূর্ণ বিষয়ের ধারণা আমরা দুটি জনপ্রিয় ফ্রেমওয়ার্ক- [TensorFlow](http://Tensorflow.org) এবং [PyTorch](http://pytorch.org) - এ কোড দিয়ে ব্যাখ্যা করব। -* ছবি এবং লেখার জন্য **নিউরাল আর্কিটেকচার**। আমরা সাম্প্রতিক মডেলগুলি আলোচনা করব, যদিও কিছু ক্ষেত্রে সর্বাধুনিকতা সামান্য কম থাকতে পারে। -* কম পরিচিত AI পদ্ধতি, যেমন **জেনেটিক অ্যালগরিদমস** এবং **মাল্টি-এজেন্ট সিস্টেমস**। +* কৃত্রিম বুদ্ধিমত্তার বিভিন্ন পদ্ধতি, যার মধ্যে রয়েছে "পুরনো সময়ের" প্রতীকী পদ্ধতি যা **জ্ঞান উপস্থাপনা** এবং যুক্তি (reasoning) ব্যবহার করে ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))। +* **নিউরাল নেটওয়ার্কস** এবং **ডীপ লার্নিং**, যা আধুনিক AI এর মূল ভিত্তি। আমরা এই গুরুত্বপূর্ণ বিষয়গুলির ধারণাগুলি কোডের মাধ্যমে দেখাব দুইটি জনপ্রিয় ফ্রেমওয়ার্ক - [TensorFlow](http://Tensorflow.org) এবং [PyTorch](http://pytorch.org) ব্যবহার করে। +* চিত্র এবং টেক্সট নিয়ে কাজ করার জন্য **নিউরাল আর্কিটেকচার**। আমরা সাম্প্রতিক মডেলগুলো আলোচনা করব যদিও কিছু অংশে সাম্প্রতিক উন্নতির থেকে সামান্য পিছিয়ে থাকতে পারে। +* কম জনপ্রিয় AI পদ্ধতি, যেমন **জেনেটিক অ্যালগরিদম** এবং **মাল্টি-এজেন্ট সিস্টেমস**। -এ পাঠ্যক্রমে যা অন্তর্ভুক্ত নেই: +এই পাঠ্যক্রমে আমরা যা কভার করব না: -> [এই কোর্সের জন্য সমস্ত অতিরিক্ত রিসোর্স আমাদের Microsoft Learn সংগ্রহে খুঁজুন](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) +> [এই কোর্সের সব অতিরিক্ত রিসোর্স আমাদের 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) অথবা [AI বিজনেস স্কুল](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum) পাঠ গ্রহণ বিবেচনা করুন, যা [INSEAD](https://www.insead.edu/) এর সাথে সহযোগিতায় তৈরি। -* **ক্লাসিক মেশিন লার্নিং**, যা আমাদের [মেশিন লার্নিং ফর বিবিনার্স পাঠ্যক্রমে](http://github.com/Microsoft/ML-for-Beginners) ভালভাবে বর্ণিত। -* ব্যবহারিক AI অ্যাপ্লিকেশন যা **[কগনিটিভ সার্ভিসেস](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** ব্যবহার করে তৈরি। এর জন্য আমরা Microsoft Learn থেকে [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 মডিউলগুলি শুরু করার পরামর্শ দিচ্ছি। -* নির্দিষ্ট ML **ক্লাউড ফ্রেমওয়ার্কস**, যেমন [Azure মেশিন লার্নিং](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), অথবা [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)। [Azure মেশিন লার্নিং দিয়ে AI সলিউশন তৈরি ও পরিচালনা](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) এবং [Azure Databricks দিয়ে মেশিন লার্নিং সলিউশন তৈরি ও পরিচালনা](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ বিবেচনা করুন। -* **কথোপকথনমূলক AI** এবং **চ্যাট বট**। একটি পৃথক [কথোপকথনমূলক AI সলিউশন তৈরি](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ আছে, এবং বিস্তারিত জন্য [এই ব্লগ পোস্ট](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) ও দেখতে পারেন। -* ডীপ লার্নিং এর পেছনের **গভীর গাণিতিকতা**। এর জন্য আমরা সুপারিশ করব [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) লেখক Ian Goodfellow, Yoshua Bengio এবং Aaron Courville, যা অনলাইনে পাওয়া যায় [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)। +* **ব্যবসায়িক ক্ষেত্রে AI** এর ব্যবহার। আপনি Microsoft Learn-এ [Introduction to AI for business users](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ 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 সাথে সহযোগিতায় তৈরি) গ্রহণ করতে পারেন। +* **ক্লাসিক মেশিন লার্নিং**, যা আমাদের [Machine Learning for Beginners Curriculum](http://github.com/Microsoft/ML-for-Beginners) এ ভালোভাবে বর্ণিত। +* **[কগনিটিভ সার্ভিসেস](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** ব্যবহার করে বাস্তব AI অ্যাপ্লিকেশন। এ জন্য Microsoft Learn এর [দৃষ্টি](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [স্বাভাবিক ভাষা প্রক্রিয়াকরণ](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum), **[Azure OpenAI সার্ভিস ব্যবহার করে জেনারেটিভ AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** এবং অন্যান্য মডিউলগুলো শুরু করার পরামর্শ দেই। +* বিশেষ 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), অথবা [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)। আপনি [Azure Machine Learning সঙ্গে মেশিন লার্নিং সমাধান তৈরি এবং পরিচালনা করা](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) এবং [Azure Databricks সঙ্গে মেশিন লার্নিং সমাধান তৈরি ও পরিচালনা করা](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ গ্রহণ করতে পারেন। +* **কথোপকথন AI** এবং **চ্যাট বটস**। এর জন্য একটি আলাদা [কথোপকথন AI সমাধান তৈরি](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ আছে, এবং বিস্তারিত জানতে [এই ব্লগ পোস্ট](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) আপনি দেখতে পারেন। +* ডীপ লার্নিংয়ের পেছনের **গাণিতিক জটিলতা**। এ জন্য আমরা সুপারিশ করব [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) বইটি, লেখক Ian Goodfellow, Yoshua Bengio এবং Aaron Courville, যা অনলাইনে [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) এ উপলব্ধ। -_ক্লাউডে AI_ বিষয়ের সহজ পরিচয়ের জন্য আপনি [Azure-এ কৃত্রিম বুদ্ধিমত্তা শুরু করুন](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ নিতে পারেন। +_এআই ইন দ্য ক্লাউড_ বিষয়গুলোর একটি কোমল পরিচিতির জন্য আপনি [Azure এর ওপর কৃত্রিম বুদ্ধিমত্তা শুরু করুন](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) শেখার পথ নিতে পারেন। -# কন্টেন্ট +# বিষয়বস্তু -| | পাঠ লিঙ্ক | PyTorch/Keras/TensorFlow | ল্যাব | +| | পাঠের লিঙ্ক | PyTorch/Keras/TensorFlow | ল্যাব | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | -| 0 | [কোর্স সেটআপ](./lessons/0-course-setup/setup.md) | [আপনার ডেভেলপমেন্ট পরিবেশ সেটআপ করুন](./lessons/0-course-setup/how-to-run.md) | | +| 0 | [কোর্স সেটআপ](./lessons/0-course-setup/setup.md) | [আপনার উন্নয়ন পরিবেশ সেটআপ করুন](./lessons/0-course-setup/how-to-run.md) | | | I | [**AI 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) / [অন্টোলজি](./lessons/2-Symbolic/FamilyOntology.ipynb) /[ধারণা গ্রাফ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | | -| III | [**নিউরাল নেটওয়ার্কসের পরিচিতি**](./lessons/3-NeuralNetworks/README.md) ||| +| 02 | [জ্ঞান উপস্থাপন এবং বিশেষজ্ঞ সিস্টেম](./lessons/2-Symbolic/README.md) | [বিশেষজ্ঞ সিস্টেম](./lessons/2-Symbolic/Animals.ipynb) / [অন্তর্জ্ঞান](./lessons/2-Symbolic/FamilyOntology.ipynb) /[ধারণা গ্রাফ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | | +| III | [**নিউরাল নেটওয়ার্কে পরিচিতি**](./lessons/3-NeuralNetworks/README.md) ||| | 03 | [পারসেপ্ট্রন](./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-লেয়ারড পারসেপ্ট্রন এবং আমাদের নিজস্ব ফ্রেমওয়ার্ক তৈরি](./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 | [ফ্রেমওয়ার্কস (PyTorch/TensorFlow) এবং ওভারফিটিংয়ের 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) | -| 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 নেটওয়ার্কস](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN আর্কিটেকচারস](./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 নেটওয়ার্কস 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 | [অটোএনকোডারস এবং 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 | [জেনারেটিভ অ্যাডভারসারিয়াল নেটওয়ার্কস 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) | +| 04 | [মাল্টি-লেয়ার্ড পারসেপ্ট্রন এবং আমাদের নিজস্ব ফ্রেমওয়ার্ক তৈরি](./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 | [ফ্রেমওয়ার্কগুলোর 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)| [মাইক্রোসফট অ্যাজিউরে কম্পিউটার ভিশন এক্সপ্লোর করুন](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) | +| 06 | [কম্পিউটার ভিশনে 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 নেটওয়ার্কস](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN স্থাপত্য](./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 | [পূর্ব-প্রশিক্ষিত 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 VAE গুলো](./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 অ্যাডভার্সিয়াল নেটওয়ার্কস 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 সনাক্তকরণ](./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। ইউ-নেট](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | | -| V | [**নেচারাল 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 নেচারাল ল্যাঙ্গুয়েজ প্রসেসিং অন্বেষণ করুন](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)| -| 13 | [টেক্সট রিপ্রেজেন্টেশন। বাউ/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 শব্দ এমবেডিং। ওয়ার্ড2ভেক এবং গ্লোভ](./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। নিজস্ব এমবেডিং প্রশিক্ষণ](./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) | +| V | [**প্রাকৃতিক ভাষা প্রক্রিয়াকরণ**](./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) | [মাইক্রোসফট অ্যাজিউরে প্রাকৃতিক ভাষা প্রক্রিয়াকরণ অন্বেষণ করুন](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)| +| 13 | [টেক্সট উপস্থাপন। বাউ/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 শব্দ 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 | [ভাষা মডেলিং। নিজের এমবেডিং প্রশিক্ষণ](./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 নেটওয়ার্কস](./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 নেটওয়ার্কস](./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 | [ট্রান্সফর্মারস। বার্ট।](./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) | | +| 18 | [ট্রান্সফরমার। 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 এনটিটি 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 | [লর্জ ল্যাঙ্গুয়েজ মডেলস, প্রম্পট প্রোগ্রামিং এবং ফিউ-শট টাস্কস](./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 প্রযুক্তি** || | -| 21 | [জেনেটিক অ্যালগরিদমস](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [নোটবুক](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | | +| 20 | [বড় ভাষার 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 কৌশলসমূহ** || | +| 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) | -| 23 | [মাল্টি-এজেন্ট সিস্টেমস](./lessons/6-Other/23-MultiagentSystems/README.md) | | | +| 23 | [মাল্টি-এজেন্ট সিস্টেম](./lessons/6-Other/23-MultiagentSystems/README.md) | | | | 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) | | +| 24 | [AI নৈতিকতা এবং দায়িত্বশীল AI](./lessons/7-Ethics/README.md) | [মাইক্রোসফট লার্ন: দায়বদ্ধ AI নীতিমালা](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | | | IX | **অতিরিক্ত** | | | | 25 | [মাল্টি-মোডাল নেটওয়ার্কস, CLIP এবং VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [নোটবুক](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | | ## প্রতিটি পাঠে রয়েছে - -* পূর্ব-পাঠের উপকরণ -* কার্যকরী জুপিটার নোটবুক, যা প্রায়ই নির্দিষ্ট ফ্রেমওয়ার্কের জন্য ( **PyTorch** বা **TensorFlow**)। কার্যকরী নোটবুকে অনেক তাত্ত্বিক উপকরণও থাকে, তাই বিষয়টি বোঝার জন্য কমপক্ষে একটি সংস্করণে (PyTorch বা TensorFlow) নোটবুকটি দেখতেই হবে। -* কিছু বিষয়ের জন্য **ল্যাব** উপলভ্য, যা আপনাকে শেখা বিষয়টি 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 আছে যা সংশ্লিষ্ট বিষয়গুলি আচ্ছাদিত করে। +* প্রাক-পঠন সামগ্রী +* executable Jupyter Notebooks, যা প্রায়শই ফ্রেমওয়ার্ক-নির্দিষ্ট (**PyTorch** বা **TensorFlow**) হয়। executable notebook-এ অনেক তাত্ত্বিক সামগ্রীও থাকে, তাই বিষয় বুঝতে হলে আপনাকে কমপক্ষে একটি সংস্করণ (PyTorch বা TensorFlow যেকোনো একটি) পড়া প্রয়োজন। +* কিছু বিষয়ের জন্য **ল্যাবস** উপলব্ধ, যা আপনাকে শেখা বিষয়টি একটি নির্দিষ্ট সমস্যায় প্রয়োগ করার সুযোগ দেয়। +* কিছু অংশে [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) মডিউলের লিঙ্ক রয়েছে যা সম্পর্কিত বিষয়গুলি আচ্ছাদিত করে। ## শুরু করা -### 🎯 AI-এ নতুন? এখানে শুরু করুন! +### 🎯 AI-তে নতুন? এখানে শুরু করুন! -আপনি যদি সম্পূর্ণ নতুন হন এবং দ্রুত, হাতে-কলমে উদাহরণ চান, তাহলে আমাদের [**শুরু করার উপযোগী উদাহরণসমূহ**](./examples/README.md) দেখুন! এতে রয়েছে: +আপনি যদি সম্পূর্ণ নতুন হন AI-তে এবং দ্রুত, হ্যান্ডস-অন উদাহরণ চান, তাহলে আমাদের [**শুরু করার জন্য উদাহরণসমূহ**](./examples/README.md) দেখুন! এর মধ্যে রয়েছে: -- 🌟 **হেলো AI ওয়ার্ল্ড** - আপনার প্রথম AI প্রোগ্রাম (প্যাটার্ন চিন্তাধারা) -- 🧠 **সহজ নিউরাল নেটওয়ার্ক** - স্ক্র্যাচ থেকে নিউরাল নেটওয়ার্ক গঠন +- 🌟 **হ্যালো AI ওয়ার্ল্ড** - আপনার প্রথম AI প্রোগ্রাম (প্যাটার্ন রিকগনিশন) +- 🧠 **সহজ নার্ভ নেটওয়ার্ক** - শূন্য থেকে একটি নার্ভ নেটওয়ার্ক তৈরি করুন +- 🖼️ **ইমেজ ক্লাসিফায়ার** - বিস্তারিত মন্তব্য সহ ইমেজ শ্রেণীবিভাগ +- 💬 **টেক্সট সেন্টিমেন্ট** - ইতিবাচক/নেতিবাচক টেক্সট বিশ্লেষণ -- 🖼️ **ইমেজ ক্লাসিফায়ার** - বিস্তারিত মন্তব্য সহ ছবি শ্রেণিবদ্ধ করা -- 💬 **টেক্সট সেন্টিমেন্ট** - ইতিবাচক/নেতিবাচক টেক্সট বিশ্লেষণ করা +এই উদাহরণগুলি আপনাকে সম্পূর্ণ পাঠ্যক্রমে প্রবেশ করার আগে AI ধারণা বোঝাতে সাহায্য করার জন্য ডিজাইন করা হয়েছে। -এই উদাহরণগুলি আপনাকে সম্পূর্ণ কারিকুলামে প্রবেশ করার আগে AI ধারণাগুলি বুঝতে সাহায্য করার জন্য ডিজাইন করা হয়েছে। +### 📚 সম্পূর্ণ পাঠ্যক্রম সেটআপ -### 📚 সম্পূর্ণ কারিকুলাম সেটআপ +- আমরা একটি [সেটআপ পাঠ](./lessons/0-course-setup/setup.md) তৈরি করেছি যাতে আপনার ডেভেলপমেন্ট পরিবেশ সেটআপে সাহায্য করা হয়। - শিক্ষকদের জন্যও আমরা একটি [পাঠ্যক্রম সেটআপ পাঠ](./lessons/0-course-setup/for-teachers.md) তৈরি করেছি! +- কীভাবে [VSCode বা Codespace-এ কোড চালানো যায়](./lessons/0-course-setup/how-to-run.md) -- আমরা একটি [সেটআপ লেসন](./lessons/0-course-setup/setup.md) তৈরি করেছি যা আপনাকে আপনার ডেভেলপমেন্ট পরিবেশ সেটআপ করতে সাহায্য করবে। - শিক্ষকদের জন্য, আমরা একটি [কারিকুলাম সেটআপ লেসন](./lessons/0-course-setup/for-teachers.md) তৈরি করেছি আপনার জন্যও! -- কীভাবে [VSCode বা Codespace-এ কোড চালাবেন](./lessons/0-course-setup/how-to-run.md) +এই ধাপগুলি অনুসরণ করুন: -এই ধাপগুলো অনুসরণ করুন: - -রিপোজিটরি ফর্ক করুন: এই পৃষ্ঠার উপরের ডানদিকে থাকা "Fork" বোতামে ক্লিক করুন। +রিপোজিটরি ফর্ক করুন: এই পৃষ্ঠার উপরের ডানদিকে "Fork" বোতামে ক্লিক করুন। রিপোজিটরি ক্লোন করুন: `git clone https://github.com/microsoft/AI-For-Beginners.git` -ভুলবেন না এই রিপো-কে স্টার (🌟) দিতে যত দ্রুত এটি খুঁজে পেতে। +ভুলবেন না এই রিপোতে (🌟) স্টার দিতে যাতে পরে সহজে খুঁজে পাবেন। ## অন্যান্য শিক্ষার্থীদের সাথে পরিচিত হন -আমাদের [অফিশিয়াল AI Discord সার্ভারে](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) যোগ দিন এবং এই কোর্সটি নিচ্ছে এমন অন্যান্য শিক্ষার্থীদের সাথে পরিচিত হন এবং নেটওয়ার্ক করুন ও সাপোর্ট পান। +আমাদের [অফিশিয়াল AI Discord সার্ভার](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)-এ যোগ দিয়ে এই কোর্স নিচ্ছে এমন অন্যান্য শিক্ষার্থীদের সাথে পরিচিত হন এবং নেটওয়ার্ক গড়ে তুলুন এবং সহায়তা নিন। -আপনার যদি পণ্য প্রতিক্রিয়া বা প্রশ্ন থাকে, তাহলে আমাদের [Azure AI Foundry ডেভেলপার ফোরাম](https://aka.ms/foundry/forum) দেখুন। +আপনি যদি প্রোডাক্ট ফিডব্যাক বা প্রশ্ন থাকে তৈরি করার সময়, তাহলে আমাদের [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) পরিদর্শন করুন। -## কুইজসমূহ +## কুইজ -> **কুইজ সম্বন্ধে একটি নোট**: সব কুইজগুলো Quiz-app ফোল্ডারে etc\quiz-app-এ অথবা [অফলাইনে এখানে](https://ff-quizzes.netlify.app/) আছে। সেগুলো লেসনের থেকে লিঙ্ক করা হয়েছে এবং কুইজ অ্যাপটি লোকালি চালানো বা Azure-এ ডিপ্লয় করা যেতে পারে; নির্দেশাবলী অনুসরণ করুন `quiz-app` ফোল্ডারে। সেগুলো ধাপে ধাপে স্থানীয়করণ হচ্ছে। +> **কুইজ সম্পর্কে একটি নোট**: সব কুইজ `etc\quiz-app` ফোল্ডারের Quiz-app-এ থাকে, অথবা [অনলাইন এখানে](https://ff-quizzes.netlify.app/)। এগুলি পাঠ্যক্রমের অন্তর্ভুক্ত কুইজ অ্যাপ থেকে লিঙ্ক করা হয়েছে; কুইজ অ্যাপ স্থানীয়ভাবে চালানো যায় বা Azure-এ ডিপ্লয় করা যায়; `quiz-app` ফোল্ডারে নির্দেশাবলী অনুসরণ করুন। এগুলি ক্রমশ স্থানীয়কৃত হচ্ছে। -## সাহায্য চাওয়া হচ্ছে +## সাহায্য প্রয়োজন -আপনার যদি কোনো পরামর্শ থাকে বা বানান/কোড ত্রুটি পেয়ে থাকেন, তাহলে একটি ইস্যু তুলুন অথবা একটি পুল রিকয়েস্ট তৈরি করুন। +আপনার কি কোনো পরামর্শ আছে বা বানানের ভুল বা কোড ত্রুটি পাওয়া গেছে? একটি ইস্যু তোলা বা একটি পুল রিকোয়েস্ট তৈরি করুন। ## বিশেষ ধন্যবাদ -* **✍️ প্রধান লেখক:** [Dmitry Soshnikov](http://soshnikov.com), PhD -* **🔥 সম্পাদক:** [Jen Looper](https://twitter.com/jenlooper), PhD +* **✍️ প্রধান লেখক:** [Dmitry Soshnikov](http://soshnikov.com), পিএইচডি +* **🔥 সম্পাদক:** [Jen Looper](https://twitter.com/jenlooper), পিএইচডি * **🎨 স্কেচনোট ইলাস্ট্রেটর:** [Tomomi Imura](https://twitter.com/girlie_mac) * **✅ কুইজ নির্মাতা:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/) -* **🙏 প্রধান অবদানকারীরা:** [Evgenii Pishchik](https://github.com/Pe4enIks) +* **🙏 প্রধান অবদানকারী:** [Evgenii Pishchik](https://github.com/Pe4enIks) -## অন্যান্য কারিকুলাম +## অন্যান্য পাঠ্যক্রম -আমাদের টিম অন্যান্য কারিকুলামও তৈরি করে! দেখুন: +আমাদের দল অন্যান্য পাঠ্যক্রমও তৈরি করে! দেখুন: ### LangChain @@ -181,7 +189,7 @@ _ক্লাউডে AI_ বিষয়ের সহজ পরিচয়ে --- -### জেনারেটিভ AI সিরিজ +### Generative AI Series [![Generative AI for Beginners](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) [![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) [![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) @@ -189,7 +197,7 @@ _ক্লাউডে AI_ বিষয়ের সহজ পরিচয়ে --- -### মূল শেখার +### Core Learning [![ML for Beginners](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) [![Data Science for Beginners](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) [![AI for Beginners](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) @@ -200,25 +208,25 @@ _ক্লাউডে AI_ বিষয়ের সহজ পরিচয়ে --- -### কপাইলট সিরিজ +### Copilot Series [![Copilot for AI Paired Programming](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) [![Copilot for C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) [![Copilot Adventure](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) -## সাহায্য কিভাবে পাবেন +## সাহায্য পাওয়া -আপনি যদি আটকে যান বা AI অ্যাপ তৈরি সম্পর্কে কোনো প্রশ্ন থাকে, তাহলে MCP সম্পর্কে আলোচনা করতে এবং অভিজ্ঞ ডেভেলপারদের সাথে মেলামেশা করতে আমাদের সহপাঠীদের সাথে যোগ দিন। এটি একটি সহায়ক কমিউনিটি যেখানে প্রশ্ন স্বাগত এবং জ্ঞান বিনিময় মুক্ত। +আপনি আটকে গেলে বা AI অ্যাপ তৈরি সম্পর্কে কোনো প্রশ্ন থাকলে MCP সম্পর্কে আলোচনায় সহকর্মী শিক্ষার্থী এবং অভিজ্ঞ ডেভেলপারদের সাথে যোগ দিন। এটি একটি সহায়ক কমিউনিটি যেখানে প্রশ্নগুলি স্বাগত এবং জ্ঞান বিনামূল্যে শেয়ার করা হয়। [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -আপনি যদি পণ্য সম্পর্কে প্রতিক্রিয়া অথবা ত্রুটি দেখেন, আমাদের দেখুন: +আপনি যদি প্রোডাক্ট ফিডব্যাক বা ত্রুটি তৈরি করার সময় পান, তাহলে দেখুন: [![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) --- -**দ্রষ্টব্য**: -এই নথিটি AI অনুবাদ সেবা [Co-op Translator](https://github.com/Azure/co-op-translator) ব্যবহার করে অনূদিত হয়েছে। যদিও আমরা যথাসম্ভব সঠিক থাকার চেষ্টা করি, তবে স্বয়ংক্রিয় অনুবাদে ত্রুটি বা ভুল থাকতে পারে। মূল ভাষায় থাকা নথিটিকেই কর্তৃপক্ষের স্বীকৃত উৎস হিসেবে গ্রহণ করা উচিত। গুরুত্বপূর্ণ তথ্যের জন্য পেশাদার মানব অনুবাদ গ্রহণ করার পরামর্শ দেওয়া হয়। এই অনুবাদের ব্যবহার থেকে উদ্ভূত কোনো ভুলবোঝাবুঝি বা ভুল ব্যাখ্যার জন্য আমরা দায়ী নই। +**অস্বীকৃতি**: +এই নথিটি AI অনুবাদ পরিষেবা [Co-op Translator](https://github.com/Azure/co-op-translator) ব্যবহার করে অনূদিত হয়েছে। আমরা যথাসাধ্য সঠিকতার চেষ্টা করি, কিন্তু স্বয়ংক্রিয় অনুবাদে ত্রুটি বা ভুল থাকতে পারে। মূল নথিটি তার নিজ ভাষায়ই কর্তAuthority সূত্র হিসাবে বিবেচনা করা উচিৎ। গুরুত্বপূর্ণ তথ্যের জন্য পেশাদার মানব অনুবাদ প্রয়োজন। অনুবাদের ব্যবহার থেকে উদ্ভূত কোনো ভুল বোঝাবুঝি বা ভুল ব্যাখ্যার জন্য আমরা দায়ী নই। \ No newline at end of file diff --git a/translations/bn/lessons/2-Symbolic/MSConceptGraph.ipynb b/translations/bn/lessons/2-Symbolic/MSConceptGraph.ipynb index 312fa22e..2bb623ff 100644 --- a/translations/bn/lessons/2-Symbolic/MSConceptGraph.ipynb +++ b/translations/bn/lessons/2-Symbolic/MSConceptGraph.ipynb @@ -1,539 +1,532 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "collapsed": true - }, - "source": [ - "## Microsoft Concept Graph - এই API আর উপলব্ধ নেই, তবে ধারণাটি বুঝতে নোটবুকটি দেখুন\n", - "\n", - "[Microsoft Concept Graph](https://concept.research.microsoft.com/) হলো ইন্টারনেট থেকে সংগৃহীত একটি বৃহৎ ট্যাক্সোনমি, যেখানে ধারণাগুলোর মধ্যে `is-a` সম্পর্ক রয়েছে।\n", - "\n", - "Context Graph দুটি রূপে পাওয়া যায়:\n", - " * ডাউনলোডের জন্য বড় টেক্সট ফাইল\n", - " * REST API\n", - "\n", - "পরিসংখ্যান:\n", - " * 5401933টি অনন্য ধারণা,\n", - " * 12551613টি অনন্য উদাহরণ\n", - " * 87603947টি `is-a` সম্পর্ক\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## ওয়েব সার্ভিস ব্যবহার করা\n", - "\n", - "ওয়েব সার্ভিস বিভিন্ন কল অফার করে যা একটি ধারণার বিভিন্ন গ্রুপে অন্তর্ভুক্ত হওয়ার সম্ভাবনা অনুমান করতে সাহায্য করে। আরও তথ্য পাওয়া যাবে [এখানে](https://concept.research.microsoft.com/Home/Api)। \n", - "এখানে একটি নমুনা URL দেওয়া হলো: `https://api.conceptnet.io/query?start=/c/en/microsoft&rel=/r/IsA&limit=10`\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "trusted": true - }, - "outputs": [], - "source": [ - "import urllib\n", - "import json\n", - "\n", - "def http(x):\n", - " response = urllib.request.urlopen(x)\n", - " data = response.read()\n", - " return data.decode('utf-8')\n", - "\n", - "def query(x):\n", - " concept = x.lower().replace(' ', '_')\n", - " url = \"https://api.conceptnet.io/query?start=/c/en/{}&rel=/r/IsA&limit=10\".format(\n", - " urllib.parse.quote(concept))\n", - " try:\n", - " result = json.loads(http(url))\n", - " except Exception:\n", - " return {}\n", - " edges = result.get('edges', [])\n", - " if not edges:\n", - " return {}\n", - " total_weight = sum(edge['weight'] for edge in edges)\n", - " if total_weight == 0:\n", - " return {}\n", - " return {edge['end']['label']: edge['weight'] / total_weight for edge in edges}\n", - "\n", - "query('microsoft')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "চলুন খবরের শিরোনামগুলোকে মূল ধারণার ভিত্তিতে শ্রেণীবদ্ধ করার চেষ্টা করি। খবরের শিরোনাম পেতে, আমরা [NewsApi.org](http://newsapi.org) সেবাটি ব্যবহার করব। এই সেবাটি ব্যবহার করতে হলে আপনাকে নিজের API কী সংগ্রহ করতে হবে - ওয়েবসাইটে যান এবং বিনামূল্যে ডেভেলপার প্ল্যানে নিবন্ধন করুন।\n" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": { - "trusted": true - }, - "outputs": [], - "source": [ - "newsapi_key = ''\n", - "def get_news(country='us'):\n", - " res = json.loads(http(\"https://newsapi.org/v2/top-headlines?country={0}&apiKey={1}\".format(country,newsapi_key)))\n", - " return res['articles']\n", - "\n", - "all_titles = [x['title'] for x in get_news('us')+get_news('gb')]" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['Covid-19 Live Updates: Vaccines and Boosters News - The New York Times',\n", - " 'Ukrainians Flee Mariupol as Russian Forces Push to Take Port City - The Wall Street Journal',\n", - " 'Bond Yields Jump, Stock Futures Rise After Powell Says Fed Is Ready to Be More Aggressive - The Wall Street Journal',\n", - " 'Putin critic Alexei Navalny found guilty by Russian court - New York Post ',\n", - " \"Supreme Court nominee Ketanji Brown Jackson will face questions at confirmation hearing's second day - CNN\",\n", - " '2 teachers killed at Swedish high school, student arrested - ABC News',\n", - " 'Clues to Covid-19’s Next Moves Come From Sewers - The Wall Street Journal',\n", - " 'Republicans to roll dice by grilling Jackson over child-pornography sentencing decisions | TheHill - The Hill',\n", - " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", - " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", - " \"US stocks whipsawed overnight after Fed Chair Powell's remarks - Fox Business\",\n", - " \"'We've learned absolutely nothing': Tests could again be in short supply if Covid surges - POLITICO\",\n", - " \"Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\",\n", - " 'China searches for victims, flight recorders after first plane crash in 12 years - Reuters',\n", - " 'Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters',\n", - " 'Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español',\n", - " 'Powers Remain and Threats Lurk as Women’s Sweet 16 Is Set - The New York Times',\n", - " 'Webb Space Telescope Begins Multi-Instrument Alignment - SciTechDaily',\n", - " \"UConn vs UCF - NCAA women's tournament second-round highlights - March Madness\",\n", - " 'Bucking Republican Trend, Indiana Governor Vetoes Transgender Sports Bill - The New York Times',\n", - " \"Maggie Fox dead: Coronation Street and Shameless actress dies after 'sudden accident' - Mirror Online - The Mirror\",\n", - " 'China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent',\n", - " 'Daniel Morgan murder: damning report condemns Met police - The Guardian',\n", - " 'What to expect from Rishi Sunak’s Spring Statement - BBC.com',\n", - " 'UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian',\n", - " \"Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\",\n", - " 'Brass Eye’s outtakes show the brutal TV comedy was the tip of an iceberg - The Guardian',\n", - " \"Vladimir Putin threatens civilians to break Mariupol's spirit - The Times\",\n", - " 'Shell U-turn on Cambo oilfield would threaten green targets, say campaigners - The Guardian',\n", - " 'St Helens dog attack: Girl aged 17 months killed at home - BBC',\n", - " \"PlayStation to buy 'Assassin's Creed' veteran Jade Raymond's Haven Studios - NME\",\n", - " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", - " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", - " 'Nintendo Switch finally has folders • Eurogamer.net - Eurogamer.net',\n", - " 'FA to “find a solution” as Liverpool fan group blasts “shambolic” Wembley travel - This Is Anfield',\n", - " 'Manchester United transfer news LIVE Erik ten Hag latest and Man Utd manager updates - Manchester Evening News',\n", - " 'Inflation raises cost of UK government borrowing in February; crude oil up again – business live - The Guardian',\n", - " 'Alexei Navalny: Kremlin critic found guilty of large-scale fraud and contempt of court by Russian court - Sky News',\n", - " \"UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\",\n", - " 'Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian']" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "all_titles" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "প্রথমত, আমরা চাই সংবাদ শিরোনাম থেকে বিশেষ্য শব্দগুলি বের করতে সক্ষম হতে। আমরা এটি করার জন্য `TextBlob` লাইব্রেরি ব্যবহার করব, যা এই ধরনের সাধারণ NLP কাজগুলোকে অনেক সহজ করে তোলে।\n" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: textblob in c:\\winapp\\miniconda3\\lib\\site-packages (0.17.1)\n", - "Requirement already satisfied: nltk>=3.1 in c:\\winapp\\miniconda3\\lib\\site-packages (from textblob) (3.5)\n", - "Requirement already satisfied: joblib in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (1.0.1)\n", - "Requirement already satisfied: regex in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (2021.11.10)\n", - "Requirement already satisfied: tqdm in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (4.61.2)\n", - "Requirement already satisfied: click in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (8.0.3)\n", - "Requirement already satisfied: colorama in c:\\winapp\\miniconda3\\lib\\site-packages (from click->nltk>=3.1->textblob) (0.4.4)\n", - "Finished.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[nltk_data] Downloading package brown to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package brown is already up-to-date!\n", - "[nltk_data] Downloading package punkt to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package punkt is already up-to-date!\n", - "[nltk_data] Downloading package wordnet to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package wordnet is already up-to-date!\n", - "[nltk_data] Downloading package averaged_perceptron_tagger to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package averaged_perceptron_tagger is already up-to-\n", - "[nltk_data] date!\n", - "[nltk_data] Downloading package conll2000 to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package conll2000 is already up-to-date!\n", - "[nltk_data] Downloading package movie_reviews to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package movie_reviews is already up-to-date!\n" - ] - } - ], - "source": [ - "import sys\n", - "!{sys.executable} -m pip install textblob\n", - "!{sys.executable} -m textblob.download_corpora\n", - "from textblob import TextBlob" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "{'covid-19 live updates': 1,\n", - " 'vaccines': 1,\n", - " 'boosters': 1,\n", - " 'york': 4,\n", - " 'ukrainians flee mariupol': 1,\n", - " 'forces push': 1,\n", - " 'port city': 1,\n", - " 'wall street journal': 3,\n", - " 'bond yields': 1,\n", - " 'futures rise': 1,\n", - " 'powell says fed': 1,\n", - " 'ready': 1,\n", - " 'be': 1,\n", - " 'aggressive': 1,\n", - " 'putin': 3,\n", - " 'alexei navalny': 2,\n", - " 'russian': 2,\n", - " 'supreme court nominee': 1,\n", - " 'ketanji brown jackson': 1,\n", - " \"confirmation hearing 's\": 1,\n", - " 'cnn': 1,\n", - " 'swedish': 1,\n", - " 'high school': 1,\n", - " 'abc': 1,\n", - " 'clues': 1,\n", - " 'covid-19': 1,\n", - " '’ s': 2,\n", - " 'moves': 1,\n", - " 'sewers': 1,\n", - " 'roll dice': 1,\n", - " 'jackson': 1,\n", - " 'decisions |': 1,\n", - " 'thehill': 1,\n", - " 'clear': 2,\n", - " 'chemical weapons': 2,\n", - " 'ukraine': 3,\n", - " 'claims president': 2,\n", - " 'biden': 2,\n", - " 'nasa': 2,\n", - " 'solar system': 2,\n", - " 'daily mail': 3,\n", - " 'us stocks': 1,\n", - " 'fed chair powell': 1,\n", - " \"'s remarks\": 1,\n", - " 'fox': 1,\n", - " \"'we 've\": 1,\n", - " 'tests': 1,\n", - " 'covid': 1,\n", - " 'politico': 1,\n", - " 'duchess': 1,\n", - " 'cambridge': 1,\n", - " 'swaps khaki jungle gear': 1,\n", - " 'vampire': 1,\n", - " 'wife': 1,\n", - " 'belize': 1,\n", - " 'china': 2,\n", - " 'flight recorders': 1,\n", - " 'plane crash': 1,\n", - " 'reuters': 2,\n", - " 'russian oligarch': 1,\n", - " 'abramovich': 1,\n", - " 'live': 1,\n", - " 'russia': 2,\n", - " 'stops talks': 1,\n", - " 'japan': 1,\n", - " 'español': 1,\n", - " 'powers remain': 1,\n", - " 'threats lurk': 1,\n", - " 'set': 1,\n", - " 'webb': 1,\n", - " 'telescope begins multi-instrument alignment': 1,\n", - " 'scitechdaily': 1,\n", - " 'uconn': 1,\n", - " 'ucf': 1,\n", - " 'ncaa': 1,\n", - " \"women 's tournament second-round highlights\": 1,\n", - " 'march madness': 1,\n", - " 'bucking republican trend': 1,\n", - " 'indiana': 1,\n", - " 'vetoes transgender': 1,\n", - " 'bill': 1,\n", - " 'maggie fox': 1,\n", - " 'coronation': 1,\n", - " 'shameless': 1,\n", - " \"'sudden accident\": 1,\n", - " 'mirror online': 1,\n", - " 'mirror': 2,\n", - " 'plane crash –': 1,\n", - " 'search': 1,\n", - " 'moment flight': 1,\n", - " 'daniel morgan': 1,\n", - " 'report condemns': 1,\n", - " 'met': 1,\n", - " 'guardian': 6,\n", - " 'rishi sunak': 1,\n", - " '’ s spring': 1,\n", - " 'statement': 1,\n", - " 'bbc.com': 1,\n", - " 'uk': 3,\n", - " 'ireland': 1,\n", - " 'euro': 1,\n", - " 'vladimir putin': 2,\n", - " \"'s 'lover\": 1,\n", - " 'brass eye': 1,\n", - " '’ s outtakes': 1,\n", - " 'brutal tv comedy': 1,\n", - " 'threatens civilians': 1,\n", - " 'mariupol': 1,\n", - " \"'s spirit\": 1,\n", - " 'shell u-turn': 1,\n", - " 'cambo': 1,\n", - " 'green targets': 1,\n", - " 'st helens': 1,\n", - " 'dog attack': 1,\n", - " 'girl': 1,\n", - " 'bbc': 1,\n", - " 'playstation': 1,\n", - " \"'assassin 's\": 1,\n", - " 'creed': 1,\n", - " 'jade raymond': 1,\n", - " 'haven studios': 1,\n", - " 'nme': 1,\n", - " 'nintendo switch': 1,\n", - " 'folders •': 1,\n", - " 'eurogamer.net': 2,\n", - " 'fa': 1,\n", - " 'solution ”': 1,\n", - " 'liverpool': 1,\n", - " 'fan group blasts “ shambolic ”': 1,\n", - " 'wembley': 1,\n", - " 'anfield': 1,\n", - " 'manchester': 1,\n", - " 'live erik': 1,\n", - " 'hag': 1,\n", - " 'utd': 1,\n", - " 'manager updates': 1,\n", - " 'manchester evening': 1,\n", - " 'inflation': 1,\n", - " 'government borrowing': 1,\n", - " 'february': 1,\n", - " 'crude oil': 1,\n", - " '– business': 1,\n", - " 'kremlin': 1,\n", - " 'large-scale fraud': 1,\n", - " 'sky': 1,\n", - " 'natural gas': 1,\n", - " 'gazprom': 1,\n", - " 'retail unit': 1,\n", - " 'insider': 1,\n", - " 'zaghari-ratcliffe': 1,\n", - " 'hunt': 1,\n", - " 'iran': 1,\n", - " 'debt payment': 1}" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "w = {}\n", - "for x in all_titles:\n", - " for n in TextBlob(x).noun_phrases:\n", - " if n in w:\n", - " w[n].append(x)\n", - " else:\n", - " w[n]=[x]\n", - "{ x:len(w[x]) for x in w.keys()}" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "আমরা দেখতে পাচ্ছি যে বিশেষ্যগুলি আমাদের বড় থিম্যাটিক গ্রুপ দেয় না। চলুন বিশেষ্যগুলিকে ধারণা গ্রাফ থেকে প্রাপ্ত আরও সাধারণ শব্দ দিয়ে প্রতিস্থাপন করি। এটি কিছুটা সময় নেবে, কারণ আমরা প্রতিটি বিশেষ্য বাক্যাংশের জন্য REST কল করছি।\n" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": { - "trusted": true - }, - "outputs": [], - "source": [ - "w = {}\n", - "for x in all_titles:\n", - " for noun in TextBlob(x).noun_phrases:\n", - " terms = query(noun)\n", - " for term in [u for u in terms.keys() if terms[u]>0.1]:\n", - " if term in w:\n", - " w[term].append(x)\n", - " else:\n", - " w[term]=[x]" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "{'city': 9,\n", - " 'brand': 4,\n", - " 'place': 9,\n", - " 'town': 4,\n", - " 'factor': 4,\n", - " 'film': 4,\n", - " 'nation': 11,\n", - " 'state': 5,\n", - " 'person': 4,\n", - " 'organization': 5,\n", - " 'publication': 10,\n", - " 'market': 5,\n", - " 'economy': 4,\n", - " 'company': 6,\n", - " 'newspaper': 6,\n", - " 'relationship': 6}" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "{ x:len(w[x]) for x in w.keys() if len(w[x])>3}" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "ECONOMY:\n", - "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", - "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", - "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", - "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", - "\n", - "NATION:\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", - "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", - "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", - "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", - "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", - "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", - "UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian\n", - "Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", - "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", - "Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian\n", - "\n", - "PERSON:\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", - "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", - "Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n" - ] - } - ], - "source": [ - "print('\\nECONOMY:\\n'+'\\n'.join(w['economy']))\n", - "print('\\nNATION:\\n'+'\\n'.join(w['nation']))\n", - "print('\\nPERSON:\\n'+'\\n'.join(w['person']))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n---\n\n**অস্বীকৃতি**: \nএই নথিটি AI অনুবাদ পরিষেবা [Co-op Translator](https://github.com/Azure/co-op-translator) ব্যবহার করে অনুবাদ করা হয়েছে। আমরা যথাসাধ্য সঠিকতার জন্য চেষ্টা করি, তবে অনুগ্রহ করে মনে রাখবেন যে স্বয়ংক্রিয় অনুবাদে ত্রুটি বা অসঙ্গতি থাকতে পারে। মূল ভাষায় থাকা নথিটিকে প্রামাণিক উৎস হিসেবে বিবেচনা করা উচিত। গুরুত্বপূর্ণ তথ্যের জন্য, পেশাদার মানব অনুবাদ সুপারিশ করা হয়। এই অনুবাদ ব্যবহারের ফলে কোনো ভুল বোঝাবুঝি বা ভুল ব্যাখ্যা হলে আমরা দায়বদ্ধ থাকব না।\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3.7.4 64-bit (conda)", - "metadata": { - "interpreter": { - "hash": "86193a1ab0ba47eac1c69c1756090baa3b420b3eea7d4aafab8b85f8b312f0c5" - } - }, - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.5" - }, - "coopTranslator": { - "original_hash": "7b3f1fc049371bcf8649ac9fefdf0413", - "translation_date": "2025-10-03T18:52:50+00:00", - "source_file": "lessons/2-Symbolic/MSConceptGraph.ipynb", - "language_code": "bn" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "## ConceptNet ব্যবহার করে ধারণা গ্রাফ\n", + "\n", + "> **বিঃদ্রঃ:** মূল [Microsoft Concept Graph](https://concept.research.microsoft.com/) API আর উপলব্ধ নেই। এই নোটবুকটি [ConceptNet](https://conceptnet.io/) ব্যবহার করার জন্য আপডেট করা হয়েছে, যা স্বল্প `is-a` সম্পর্ক সহ ধারণাগুলির মধ্যে একটি স্বতন্ত্রভাবে উপলব্ধ খোলা জ্ঞান গ্রাফ।\n", + "\n", + "[ConceptNet](https://conceptnet.io/) হল ধারণার একটি বড় সেমান্টিক নেটওয়ার্ক যার মধ্যে সম্পর্ক যেমন `IsA`, `PartOf`, `UsedFor` ইত্যাদি রয়েছে। এটি উপলব্ধ:\n", + " * একটি ডাউনলোডযোগ্য ডেটা ফাইল হিসেবে\n", + " * একটি REST API (কোন API কী প্রয়োজন নেই)\n", + "\n", + "ConceptNet এর পরিসংখ্যান:\n", + " * ৮ মিলিয়নেরও বেশি নোড\n", + " * ৮৩টি ভাষায় ২১+ মিলিয়ন এজ্‌স্‌\n" + ] }, - "nbformat": 4, - "nbformat_minor": 2 + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## ConceptNet ওয়েব পরিষেবা ব্যবহার করা\n", + "\n", + "[ConceptNet](https://conceptnet.io/) ধারণাগুলোর মধ্যে `is-a` (IsA) সম্পর্কগুলি অনুসন্ধান করার জন্য একটি REST API প্রদান করে। কোনও API কী প্রয়োজন নেই।\n", + "এখানে কল করার নমুনা URL দেওয়া হলো: `https://api.conceptnet.io/query?start=/c/en/microsoft&rel=/r/IsA&limit=10`\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "import urllib\n", + "import json\n", + "\n", + "def http(x):\n", + " response = urllib.request.urlopen(x)\n", + " data = response.read()\n", + " return data.decode('utf-8')\n", + "\n", + "def query(x):\n", + " concept = x.lower().replace(' ', '_')\n", + " url = \"https://api.conceptnet.io/query?start=/c/en/{}&rel=/r/IsA&limit=10\".format(\n", + " urllib.parse.quote(concept))\n", + " try:\n", + " result = json.loads(http(url))\n", + " except Exception:\n", + " return {}\n", + " edges = result.get('edges', [])\n", + " if not edges:\n", + " return {}\n", + " total_weight = sum(edge['weight'] for edge in edges)\n", + " if total_weight == 0:\n", + " return {}\n", + " return {edge['end']['label']: edge['weight'] / total_weight for edge in edges}\n", + "\n", + "query('microsoft')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "চলুন নিউজ শিরোনাম গুলো প্যারেন্ট ধারণার মাধ্যমে শ্রেণীবদ্ধ করার চেষ্টা করি। নিউজ শিরোনাম পেতে আমরা [NewsApi.org](http://newsapi.org) সার্ভিস ব্যবহার করব। সার্ভিস ব্যবহার করার জন্য আপনাকে আপনার নিজস্ব API কী নিতে হবে - ওয়েবসাইটে যান এবং ফ্রিতে ডেভেলপার প্ল্যানে রেজিস্টার করুন।\n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "newsapi_key = ''\n", + "def get_news(country='us'):\n", + " res = json.loads(http(\"https://newsapi.org/v2/top-headlines?country={0}&apiKey={1}\".format(country,newsapi_key)))\n", + " return res['articles']\n", + "\n", + "all_titles = [x['title'] for x in get_news('us')+get_news('gb')]" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Covid-19 Live Updates: Vaccines and Boosters News - The New York Times',\n", + " 'Ukrainians Flee Mariupol as Russian Forces Push to Take Port City - The Wall Street Journal',\n", + " 'Bond Yields Jump, Stock Futures Rise After Powell Says Fed Is Ready to Be More Aggressive - The Wall Street Journal',\n", + " 'Putin critic Alexei Navalny found guilty by Russian court - New York Post ',\n", + " \"Supreme Court nominee Ketanji Brown Jackson will face questions at confirmation hearing's second day - CNN\",\n", + " '2 teachers killed at Swedish high school, student arrested - ABC News',\n", + " 'Clues to Covid-19’s Next Moves Come From Sewers - The Wall Street Journal',\n", + " 'Republicans to roll dice by grilling Jackson over child-pornography sentencing decisions | TheHill - The Hill',\n", + " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", + " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", + " \"US stocks whipsawed overnight after Fed Chair Powell's remarks - Fox Business\",\n", + " \"'We've learned absolutely nothing': Tests could again be in short supply if Covid surges - POLITICO\",\n", + " \"Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\",\n", + " 'China searches for victims, flight recorders after first plane crash in 12 years - Reuters',\n", + " 'Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters',\n", + " 'Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español',\n", + " 'Powers Remain and Threats Lurk as Women’s Sweet 16 Is Set - The New York Times',\n", + " 'Webb Space Telescope Begins Multi-Instrument Alignment - SciTechDaily',\n", + " \"UConn vs UCF - NCAA women's tournament second-round highlights - March Madness\",\n", + " 'Bucking Republican Trend, Indiana Governor Vetoes Transgender Sports Bill - The New York Times',\n", + " \"Maggie Fox dead: Coronation Street and Shameless actress dies after 'sudden accident' - Mirror Online - The Mirror\",\n", + " 'China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent',\n", + " 'Daniel Morgan murder: damning report condemns Met police - The Guardian',\n", + " 'What to expect from Rishi Sunak’s Spring Statement - BBC.com',\n", + " 'UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian',\n", + " \"Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\",\n", + " 'Brass Eye’s outtakes show the brutal TV comedy was the tip of an iceberg - The Guardian',\n", + " \"Vladimir Putin threatens civilians to break Mariupol's spirit - The Times\",\n", + " 'Shell U-turn on Cambo oilfield would threaten green targets, say campaigners - The Guardian',\n", + " 'St Helens dog attack: Girl aged 17 months killed at home - BBC',\n", + " \"PlayStation to buy 'Assassin's Creed' veteran Jade Raymond's Haven Studios - NME\",\n", + " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", + " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", + " 'Nintendo Switch finally has folders • Eurogamer.net - Eurogamer.net',\n", + " 'FA to “find a solution” as Liverpool fan group blasts “shambolic” Wembley travel - This Is Anfield',\n", + " 'Manchester United transfer news LIVE Erik ten Hag latest and Man Utd manager updates - Manchester Evening News',\n", + " 'Inflation raises cost of UK government borrowing in February; crude oil up again – business live - The Guardian',\n", + " 'Alexei Navalny: Kremlin critic found guilty of large-scale fraud and contempt of court by Russian court - Sky News',\n", + " \"UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\",\n", + " 'Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian']" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "all_titles" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "প্রথমত, আমরা নিউজ শিরোনাম থেকে বিশেষণ পদগুলি বের করতে সক্ষম হতে চাই। আমরা এই কাজের জন্য `TextBlob` লাইব্রেরি ব্যবহার করব, যা এই ধরনের অনেক সাধারণ এনএলপি কাজকে সহজ করে তোলে।\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: textblob in c:\\winapp\\miniconda3\\lib\\site-packages (0.17.1)\n", + "Requirement already satisfied: nltk>=3.1 in c:\\winapp\\miniconda3\\lib\\site-packages (from textblob) (3.5)\n", + "Requirement already satisfied: joblib in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (1.0.1)\n", + "Requirement already satisfied: regex in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (2021.11.10)\n", + "Requirement already satisfied: tqdm in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (4.61.2)\n", + "Requirement already satisfied: click in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (8.0.3)\n", + "Requirement already satisfied: colorama in c:\\winapp\\miniconda3\\lib\\site-packages (from click->nltk>=3.1->textblob) (0.4.4)\n", + "Finished.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[nltk_data] Downloading package brown to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package brown is already up-to-date!\n", + "[nltk_data] Downloading package punkt to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package punkt is already up-to-date!\n", + "[nltk_data] Downloading package wordnet to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package averaged_perceptron_tagger to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package averaged_perceptron_tagger is already up-to-\n", + "[nltk_data] date!\n", + "[nltk_data] Downloading package conll2000 to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package conll2000 is already up-to-date!\n", + "[nltk_data] Downloading package movie_reviews to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package movie_reviews is already up-to-date!\n" + ] + } + ], + "source": [ + "import sys\n", + "!{sys.executable} -m pip install textblob\n", + "!{sys.executable} -m textblob.download_corpora\n", + "from textblob import TextBlob" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'covid-19 live updates': 1,\n", + " 'vaccines': 1,\n", + " 'boosters': 1,\n", + " 'york': 4,\n", + " 'ukrainians flee mariupol': 1,\n", + " 'forces push': 1,\n", + " 'port city': 1,\n", + " 'wall street journal': 3,\n", + " 'bond yields': 1,\n", + " 'futures rise': 1,\n", + " 'powell says fed': 1,\n", + " 'ready': 1,\n", + " 'be': 1,\n", + " 'aggressive': 1,\n", + " 'putin': 3,\n", + " 'alexei navalny': 2,\n", + " 'russian': 2,\n", + " 'supreme court nominee': 1,\n", + " 'ketanji brown jackson': 1,\n", + " \"confirmation hearing 's\": 1,\n", + " 'cnn': 1,\n", + " 'swedish': 1,\n", + " 'high school': 1,\n", + " 'abc': 1,\n", + " 'clues': 1,\n", + " 'covid-19': 1,\n", + " '’ s': 2,\n", + " 'moves': 1,\n", + " 'sewers': 1,\n", + " 'roll dice': 1,\n", + " 'jackson': 1,\n", + " 'decisions |': 1,\n", + " 'thehill': 1,\n", + " 'clear': 2,\n", + " 'chemical weapons': 2,\n", + " 'ukraine': 3,\n", + " 'claims president': 2,\n", + " 'biden': 2,\n", + " 'nasa': 2,\n", + " 'solar system': 2,\n", + " 'daily mail': 3,\n", + " 'us stocks': 1,\n", + " 'fed chair powell': 1,\n", + " \"'s remarks\": 1,\n", + " 'fox': 1,\n", + " \"'we 've\": 1,\n", + " 'tests': 1,\n", + " 'covid': 1,\n", + " 'politico': 1,\n", + " 'duchess': 1,\n", + " 'cambridge': 1,\n", + " 'swaps khaki jungle gear': 1,\n", + " 'vampire': 1,\n", + " 'wife': 1,\n", + " 'belize': 1,\n", + " 'china': 2,\n", + " 'flight recorders': 1,\n", + " 'plane crash': 1,\n", + " 'reuters': 2,\n", + " 'russian oligarch': 1,\n", + " 'abramovich': 1,\n", + " 'live': 1,\n", + " 'russia': 2,\n", + " 'stops talks': 1,\n", + " 'japan': 1,\n", + " 'español': 1,\n", + " 'powers remain': 1,\n", + " 'threats lurk': 1,\n", + " 'set': 1,\n", + " 'webb': 1,\n", + " 'telescope begins multi-instrument alignment': 1,\n", + " 'scitechdaily': 1,\n", + " 'uconn': 1,\n", + " 'ucf': 1,\n", + " 'ncaa': 1,\n", + " \"women 's tournament second-round highlights\": 1,\n", + " 'march madness': 1,\n", + " 'bucking republican trend': 1,\n", + " 'indiana': 1,\n", + " 'vetoes transgender': 1,\n", + " 'bill': 1,\n", + " 'maggie fox': 1,\n", + " 'coronation': 1,\n", + " 'shameless': 1,\n", + " \"'sudden accident\": 1,\n", + " 'mirror online': 1,\n", + " 'mirror': 2,\n", + " 'plane crash –': 1,\n", + " 'search': 1,\n", + " 'moment flight': 1,\n", + " 'daniel morgan': 1,\n", + " 'report condemns': 1,\n", + " 'met': 1,\n", + " 'guardian': 6,\n", + " 'rishi sunak': 1,\n", + " '’ s spring': 1,\n", + " 'statement': 1,\n", + " 'bbc.com': 1,\n", + " 'uk': 3,\n", + " 'ireland': 1,\n", + " 'euro': 1,\n", + " 'vladimir putin': 2,\n", + " \"'s 'lover\": 1,\n", + " 'brass eye': 1,\n", + " '’ s outtakes': 1,\n", + " 'brutal tv comedy': 1,\n", + " 'threatens civilians': 1,\n", + " 'mariupol': 1,\n", + " \"'s spirit\": 1,\n", + " 'shell u-turn': 1,\n", + " 'cambo': 1,\n", + " 'green targets': 1,\n", + " 'st helens': 1,\n", + " 'dog attack': 1,\n", + " 'girl': 1,\n", + " 'bbc': 1,\n", + " 'playstation': 1,\n", + " \"'assassin 's\": 1,\n", + " 'creed': 1,\n", + " 'jade raymond': 1,\n", + " 'haven studios': 1,\n", + " 'nme': 1,\n", + " 'nintendo switch': 1,\n", + " 'folders •': 1,\n", + " 'eurogamer.net': 2,\n", + " 'fa': 1,\n", + " 'solution ”': 1,\n", + " 'liverpool': 1,\n", + " 'fan group blasts “ shambolic ”': 1,\n", + " 'wembley': 1,\n", + " 'anfield': 1,\n", + " 'manchester': 1,\n", + " 'live erik': 1,\n", + " 'hag': 1,\n", + " 'utd': 1,\n", + " 'manager updates': 1,\n", + " 'manchester evening': 1,\n", + " 'inflation': 1,\n", + " 'government borrowing': 1,\n", + " 'february': 1,\n", + " 'crude oil': 1,\n", + " '– business': 1,\n", + " 'kremlin': 1,\n", + " 'large-scale fraud': 1,\n", + " 'sky': 1,\n", + " 'natural gas': 1,\n", + " 'gazprom': 1,\n", + " 'retail unit': 1,\n", + " 'insider': 1,\n", + " 'zaghari-ratcliffe': 1,\n", + " 'hunt': 1,\n", + " 'iran': 1,\n", + " 'debt payment': 1}" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "w = {}\n", + "for x in all_titles:\n", + " for n in TextBlob(x).noun_phrases:\n", + " if n in w:\n", + " w[n].append(x)\n", + " else:\n", + " w[n]=[x]\n", + "{ x:len(w[x]) for x in w.keys()}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "আমরা দেখতে পাচ্ছি যে নামগুলি আমাদের বড় থিম্যাটিক গ্রুপ দেয় না। চলুন নামগুলি পরিবর্তে ধারণা গ্রাফ থেকে প্রাপ্ত আরও সাধারণ শব্দগুলি ব্যবহার করি। এটি কিছু সময় নেবে, কারণ আমরা প্রতিটি নাম পদার্থের জন্য REST কল করছি।\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "w = {}\n", + "for x in all_titles:\n", + " for noun in TextBlob(x).noun_phrases:\n", + " terms = query(noun)\n", + " for term in [u for u in terms.keys() if terms[u]>0.1]:\n", + " if term in w:\n", + " w[term].append(x)\n", + " else:\n", + " w[term]=[x]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'city': 9,\n", + " 'brand': 4,\n", + " 'place': 9,\n", + " 'town': 4,\n", + " 'factor': 4,\n", + " 'film': 4,\n", + " 'nation': 11,\n", + " 'state': 5,\n", + " 'person': 4,\n", + " 'organization': 5,\n", + " 'publication': 10,\n", + " 'market': 5,\n", + " 'economy': 4,\n", + " 'company': 6,\n", + " 'newspaper': 6,\n", + " 'relationship': 6}" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "{ x:len(w[x]) for x in w.keys() if len(w[x])>3}" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "ECONOMY:\n", + "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", + "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", + "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", + "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", + "\n", + "NATION:\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", + "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", + "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", + "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", + "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", + "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", + "UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian\n", + "Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", + "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", + "Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian\n", + "\n", + "PERSON:\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", + "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", + "Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n" + ] + } + ], + "source": [ + "print('\\nECONOMY:\\n'+'\\n'.join(w['economy']))\n", + "print('\\nNATION:\\n'+'\\n'.join(w['nation']))\n", + "print('\\nPERSON:\\n'+'\\n'.join(w['person']))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n\n\n**বিস্তারিত দায়িত্ব পরিহার**: \nএই নথিটি AI অনুবাদ সেবা [Co-op Translator](https://github.com/Azure/co-op-translator) ব্যবহার করে অনূদিত হয়েছে। যদিও আমরা যথাসম্ভব সঠিকতার চেষ্টা করি, দয়া করে মনে রাখবেন যে স্বয়ংক্রিয় অনুবাদে কিছু ভুল বা অসামঞ্জস্যতা থাকতে পারে। মূল নথিটি তার নিজ ভাষাতেই প্রধান এবং প্রামাণিক উৎস হিসেবে বিবেচিত হবে। অত্যন্ত গুরুত্বপূর্ণ তথ্যের জন্য পেশাদার মানব অনুবাদের পরামর্শ দেওয়া হয়। এই অনুবাদের ব্যবহার থেকে সৃষ্ট কোনো ভুল বোঝাবুঝি বা ভুল ব্যাখ্যার জন্য আমরা দায়বদ্ধ নই।\n\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.7.4 64-bit (conda)", + "metadata": { + "interpreter": { + "hash": "86193a1ab0ba47eac1c69c1756090baa3b420b3eea7d4aafab8b85f8b312f0c5" + } + }, + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 } \ No newline at end of file diff --git a/translations/hi/.co-op-translator.json b/translations/hi/.co-op-translator.json index 44b23de2..77490dfc 100644 --- a/translations/hi/.co-op-translator.json +++ b/translations/hi/.co-op-translator.json @@ -6,8 +6,8 @@ "language_code": "hi" }, "README.md": { - "original_hash": "75fe3383afc51eaa84b82ace619ffea7", - "translation_date": "2026-02-06T07:48:27+00:00", + "original_hash": "9eaca839b0b3f6d7f0a195fd33cebd30", + "translation_date": "2026-02-28T09:59:06+00:00", "source_file": "README.md", "language_code": "hi" }, @@ -89,6 +89,12 @@ "source_file": "lessons/1-Intro/assignment.md", "language_code": "hi" }, + "lessons/2-Symbolic/MSConceptGraph.ipynb": { + "original_hash": "e5690bbc6e5119a96a8172ec7261db67", + "translation_date": "2026-02-28T09:56:07+00:00", + "source_file": "lessons/2-Symbolic/MSConceptGraph.ipynb", + "language_code": "hi" + }, "lessons/2-Symbolic/README.md": { "original_hash": "f9f06b266b8b2bfc6b8792ff2bb1bea4", "translation_date": "2026-01-15T13:01:55+00:00", diff --git a/translations/hi/README.md b/translations/hi/README.md index da159420..573fedad 100644 --- a/translations/hi/README.md +++ b/translations/hi/README.md @@ -12,159 +12,169 @@ [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -# शुरुआती लोगों के लिए कृत्रिम बुद्धिमत्ता - एक पाठ्यक्रम +# शुरुआती लोगों के लिए आर्टिफिशियल इंटेलिजेंस - एक पाठ्यक्रम |![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](https://github.com/microsoft/AI-For-Beginners/raw/main/lessons/sketchnotes/ai-overview.png)| |:---:| -| शुरुआती लोगों के लिए AI - _स्केचनोट द्वारा [@girlie_mac](https://twitter.com/girlie_mac)_ | +| शुरुआती लोगों के लिए AI - _स्केचनोट [@girlie_mac](https://twitter.com/girlie_mac) द्वारा_ | + +हमारे 12 सप्ताह, 24-लेसन के पाठ्यक्रम के साथ **आर्टिफिशियल इंटेलिजेंस** (AI) की दुनिया को खोजें! इसमें व्यावहारिक पाठ, क्विज़ और लैब शामिल हैं। यह पाठ्यक्रम शुरुआती दोस्तों के लिए उपयुक्त है और TensorFlow और PyTorch जैसे टूल्स, साथ ही AI में नैतिकता को भी कवर करता है। -हमारे 12 सप्ताह, 24-लेसन पाठ्यक्रम के साथ **कृत्रिम बुद्धिमत्ता** (AI) की दुनिया का पता लगाएं! इसमें व्यावहारिक पाठ, क्विज़ और प्रयोगशालाएं शामिल हैं। यह पाठ्यक्रम शुरुआती लोगों के लिए उपयुक्त है और इसमें TensorFlow और PyTorch जैसे टूल्स के साथ-साथ AI में नैतिकता को भी कवर किया गया है। ### 🌐 बहुभाषी समर्थन -#### GitHub Action के माध्यम से समर्थित (स्वचालित और हमेशा अपडेट) +#### GitHub Action के माध्यम से समर्थित (स्वचालित और हमेशा अद्यतन) [Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](../zh-HK/README.md) | [Chinese (Traditional, Macau)](../zh-MO/README.md) | [Chinese (Traditional, Taiwan)](../zh-TW/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](./README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../pt-BR/README.md) | [Portuguese (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) > **स्थानीय रूप से क्लोन करना पसंद करते हैं?** - -> इस रिपॉजिटरी में 50+ भाषा अनुवाद शामिल हैं जो डाउनलोड साइज़ को काफी बढ़ा देते हैं। अनुवादों के बिना क्लोन करने के लिए sparse checkout का उपयोग करें: +> +> इस रिपॉजिटरी में 50+ भाषा अनुवाद शामिल हैं, जो डाउनलोड आकार को काफी बढ़ा देते हैं। अनुवाद के बिना क्लोन करने के लिए, sparse checkout का उपयोग करें: +> +> **Bash / macOS / Linux:** > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git > cd AI-For-Beginners > git sparse-checkout set --no-cone '/*' '!translations' '!translated_images' > ``` -> यह आपको इस कोर्स को पूरा करने के लिए आवश्यक सभी चीज़ें बहुत तेज़ डाउनलोड के साथ देता है। +> +> **CMD (Windows):** +> ```cmd +> git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git +> cd AI-For-Beginners +> git sparse-checkout set --no-cone "/*" "!translations" "!translated_images" +> ``` +> +> इससे आपको पाठ्यक्रम पूरा करने के लिए आवश्यक सभी सामग्री मिलेंगी, वह भी बहुत तेज डाउनलोड के साथ। -**यदि आप अतिरिक्त अनुवाद भाषाओं का समर्थन चाहते हैं, तो वे [यहाँ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) सूचीबद्ध हैं** +**यदि आप अतिरिक्त अनुवाद भाषाओं का समर्थन चाहते हैं तो वे [यहाँ](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md) सूचीबद्ध हैं** -## समुदाय में शामिल हों +## समुदाय से जुड़ें [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) ## आप क्या सीखेंगे -**[कोर्स का माइंडमैप](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** +**[पाठ्यक्रम का माइंडमैप](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** इस पाठ्यक्रम में, आप सीखेंगे: -* कृत्रिम बुद्धिमत्ता के विभिन्न दृष्टिकोण, जिनमें "पुराना" प्रतीकात्मक दृष्टिकोण जैसे **ज्ञान प्रतिनिधित्व** और तर्कशक्ति शामिल हैं ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))। -* **न्यूरल नेटवर्क्स** और **डीप लर्निंग**, जो आधुनिक AI का मूल हैं। हम इन महत्वपूर्ण विषयों के पीछे की अवधारणाओं को दो लोकप्रिय फ्रेमवर्क - [TensorFlow](http://Tensorflow.org) और [PyTorch](http://pytorch.org) - में कोड के माध्यम से चित्रित करेंगे। -* छवियों और टेक्स्ट के साथ काम करने के लिए **न्यूरल आर्किटेक्चर**। हम हाल के मॉडलों को कवर करेंगे लेकिन हो सकता है कि अत्याधुनिक स्तर पर थोड़ी कमी हो। -* कम लोकप्रिय AI दृष्टिकोण, जैसे **जेनेटिक एल्गोरिदम** और **मल्टी-एजेंट सिस्टम्स**। +* आर्टिफिशियल इंटेलिजेंस के विभिन्न दृष्टिकोण, जिनमें "पुराना" प्रतीकात्मक दृष्टिकोण **ज्ञान प्रतिनिधित्व** और तर्क सहित ([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)) शामिल हैं। +* **न्यूरल नेटवर्क** और **डीप लर्निंग**, जो आधुनिक AI के मूल में हैं। हम इन महत्वपूर्ण विषयों के पीछे की अवधारणाओं को दो सबसे लोकप्रिय फ्रेमवर्क - [TensorFlow](http://Tensorflow.org) और [PyTorch](http://pytorch.org) - में कोड के उपयोग से समझाएंगे। +* छवियों और पाठ के साथ काम करने के लिए **न्यूरल आर्किटेक्चर**। हम हाल के मॉडल कवर करेंगे, लेकिन संभवतः अत्याधुनिक में थोड़ा कम होंगे। +* कम लोकप्रिय AI दृष्टिकोण, जैसे कि **जेनेटिक एल्गोरिदम** और **मल्टी-एजेंट सिस्टम**। -इस पाठ्यक्रम में हम क्या नहीं कवर करेंगे: +इस पाठ्यक्रम में हम क्या शामिल नहीं करेंगे: -> [इस कोर्स के लिए सभी अतिरिक्त संसाधन Microsoft Learn संग्रह में खोजें](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) +> [इस कोर्स के सभी अतिरिक्त संसाधन हमारी Microsoft Learn संग्रह में देखें](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) -* **व्यवसाय में AI** के बिजनेस केस। आप Microsoft Learn पर [व्यवसाय उपयोगकर्ताओं के लिए AI का परिचय](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) सीखने के पथ या [AI बिजनेस स्कूल](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), जिसे [INSEAD](https://www.insead.edu/) के साथ सहयोग में विकसित किया गया है, लेना consider कर सकते हैं। -* **क्लासिक मशीन लर्निंग**, जो हमारे [डबलब्लू मशीन लर्निंग फॉर बिगिनर्स पाठ्यक्रम](http://github.com/Microsoft/ML-for-Beginners) में अच्छी तरह से वर्णित है। -* व्यावहारिक AI अनुप्रयोग जो **[कॉग्निटिव सर्विसेज](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** का उपयोग करके बनाए गए हैं। इसके लिए, हम Microsoft Learn के [विजन](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [प्राकृतिक भाषा प्रसंस्करण](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 के साथ शुरू करने की सलाह देते 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)। आप [Azure Machine Learning के साथ मशीन लर्निंग समाधान बनाना और चलाना](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) और [Azure Databricks के साथ मशीन लर्निंग समाधान बनाना और चलाना](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) सीखने के पथ का उपयोग भी कर सकते हैं। -* **संवादी AI** और **चैट बॉट्स**। इसके लिए एक अलग [संवादी AI समाधान बनाएं](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) सीखने का पथ है, और आप अधिक विवरण के लिए [इस ब्लॉग पोस्ट](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) को भी देख सकते हैं। -* डीप लर्निंग के पीछे की **गहन गणित**। इसके लिए हम Ian Goodfellow, Yoshua Bengio और Aaron Courville की [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) की सिफारिश करते हैं, जो ऑनलाइन [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/) पर भी उपलब्ध है। +* व्यावसायिक मामलों में **AI का उपयोग**। Microsoft Learn पर [व्यावसायिक उपयोगकर्ताओं के लिए AI का परिचय](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) सीखने के रास्ते, या [AI बिजनेस स्कूल](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum), जो [INSEAD](https://www.insead.edu/) के साथ सहयोग में विकसित किया गया है, लेने पर विचार करें। +* **क्लासिक मशीन लर्निंग**, जो हमारे [शुरुआती लोगों के लिए मशीन लर्निंग पाठ्यक्रम](http://github.com/Microsoft/ML-for-Beginners) में अच्छी तरह से वर्णित 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 आपको Microsoft Learn के [दृष्टि](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum), [प्राकृतिक भाषा प्रसंस्करण](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 शुरू करने की सलाह देते 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 के साथ मशीन लर्निंग समाधान बनाएँ और संचालित करें](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) और [Azure Databricks के साथ मशीन लर्निंग समाधान बनाएँ और संचालित करें](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) सीखने के रास्ते उपयोग पर विचार करें। +* **संवादात्मक AI** और **चैट बॉट्स**। इसके लिए एक अलग [संवादात्मक AI समाधान बनाएँ](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) सीखने का रास्ता है, और आप अधिक विवरण के लिए [इस ब्लॉग पोस्ट](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) को भी देख सकते हैं। +* गहन सीखने के पीछे **गहरी गणित**। इसके लिए हम Ian Goodfellow, Yoshua Bengio, और Aaron Courville द्वारा लिखित [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) की सलाह देंगे, जो ऑनलाइन भी उपलब्ध है [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)। -_क्लाउड में AI_ विषयों के लिए एक सहज परिचय 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 पथ ले सकते हैं। +_क्लाउड में AI_ विषयों का सौम्य परिचय पाने के लिए, आप [Azure पर आर्टिफिशियल इंटेलिजेंस के साथ शुरू करें](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) सीखने के रास्ते को चुन सकते हैं। # सामग्री -| | पाठ लिंक | PyTorch/Keras/TensorFlow | प्रयोगशाला | -| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | +| | पाठ लिंक | PyTorch/Keras/TensorFlow | लैब | +| :-: | :---------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 0 | [कोर्स सेटअप](./lessons/0-course-setup/setup.md) | [अपने विकास पर्यावरण को सेटअप 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 सिस्टम](./lessons/2-Symbolic/README.md) | [विशेषज्ञ सिस्टम](./lessons/2-Symbolic/Animals.ipynb) / [ऑन्टोलॉजी](./lessons/2-Symbolic/FamilyOntology.ipynb) /[संरचना ग्राफ](./lessons/2-Symbolic/MSConceptGraph.ipynb) | | -| 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 खुद का 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 | [फ्रेमवर्क का परिचय (PyTorch/TensorFlow) और ओवरफिटिंग](./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) | [लैब](./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)| [माइक्रोसॉफ्ट एज्योर पर कंप्यूटर विज़न एक्सप्लोर 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) | [लैब](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) | -| 07 | [कॉनवल्यूशनल न्यूरल नेटवर्क्स](./lessons/4-ComputerVision/07-ConvNets/README.md) & [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) | [लैब](./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) | [लैब](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) | -| 09 | [ऑटोएन्कोडर्स और 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 | [जेनरेटिव एडवरसैरियल 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) | [लैब](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) | -| 12 | [सेमेंटिक 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 | [**प्राकृतिक भाषा संसाधन**](./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) | [माइक्रोसॉफ्ट एज्योर पर प्राकृतिक भाषा संसाधन एक्सप्लोर करें](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)| -| 13 | [टेक्स्ट 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 | [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 | [भाषा मॉडलिंग। अपनी खुद की एम्बेडिंग्स का प्रशिक्षण](./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) | [लैब](./lessons/5-NLP/15-LanguageModeling/lab/README.md) | -| 16 | [रिकर्रेंट 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 | [जेनरेटिव रिकारेंट 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) | [लैब](./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 | [नामित 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) | [लैब](./lessons/5-NLP/19-NER/lab/README.md) | -| 20 | [बड़े भाषा मॉडल, प्रॉम्प्ट प्रोग्रामिंग और कम-शॉट टास्क](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | | +| 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 | [पर्सेप्ट्रॉन](./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 पर्सेप्ट्रॉन और हमारा खुद का 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) | +| 05 | [फ्रेमवर्क का परिचय (PyTorch/TensorFlow) और ओवरफिटिंग](./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 | [कन्वॉल्यूशनल न्यूरल नेटवर्क](./lessons/4-ComputerVision/07-ConvNets/README.md) & [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 | [पूर्व-प्रशिक्षित नेटवर्क और ट्रांसफर लर्निंग](./lessons/4-ComputerVision/08-TransferLearning/README.md) और [प्रशिक्षण 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 | [जनरेटिव एडवर्सैरियल नेटवर्क 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 | [सिमेंटिक 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 | [**प्राकृतिक भाषा प्रसंस्करण**](./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 प्राकृतिक भाषा प्रसंस्करण का अन्वेषण करें](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)| +| 13 | [पाठ प्रतिनिधित्व. बोव/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 | [सिमेंटिक शब्द 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 | [भाषा मॉडलिंग. अपने स्वयं के एम्बेडिंग्स का प्रशिक्षण](./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 रिकरेंट 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 | [नामित इकाई मान्यता](./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 भाषा मॉडल, प्रॉम्प्ट प्रोग्रामिंग और फ्यू-शॉट कार्य](./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 | [जैविक एल्गोरिदम](./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) | [लैब](./lessons/6-Other/22-DeepRL/lab/README.md) | -| 23 | [मल्टी-एजेंट सिस्टम्स](./lessons/6-Other/23-MultiagentSystems/README.md) | | | +| 21 | [जेनिटिक अल्गोरिदम](./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 सिस्टम](./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** | | | -| 25 | [मल्टी-मोडल नेटवर्क्स, CLIP और VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [नोटबुक](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | | +| 25 | [मल्टी-मॉडल नेटवर्क, CLIP और VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [नोटबुक](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | | -## प्रत्येक पाठ में शामिल हैं - -* पूर्व-पठन सामग्री -* निष्पादनीय जुपिटर नोटबुक्स, जो अक्सर फ्रेमवर्क (**PyTorch** या **TensorFlow**) के अनुसार विशिष्ट होती हैं। निष्पादनीय नोटबुक में बहुत सारी सैद्धांतिक सामग्री भी होती है, इसलिए विषय को समझने के लिए आपको कम से कम एक संस्करण (PyTorch या TensorFlow) को पढ़ना आवश्यक है। -* कुछ विषयों के लिए **लैब्स** उपलब्ध हैं, जो आपको सीखी गई सामग्री को किसी विशिष्ट समस्या पर लागू करने का मौका देती हैं। -* कुछ अनुभागों में संबंधित विषयों को कवर करने वाले [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) मॉड्यूल के लिंक होते हैं। +## प्रत्येक पाठ में होता है +* पूर्व-पठन सामग्री +* निष्पादनीय Jupyter नोटबुक, जो अक्सर फ्रेमवर्क (**PyTorch** या **TensorFlow**) के लिए विशिष्ट होती हैं। निष्पादनीय नोटबुक में बहुत सारा सैद्धांतिक सामग्री भी होता है, इसलिए विषय को समझने के लिए आपको नोटबुक का कम से कम एक संस्करण (या तो PyTorch या TensorFlow) देखना आवश्यक है। +* कुछ विषयों के लिए उपलब्ध **प्रयोगशालाएं**, जो आपको आपने सीखे हुए सामग्री को एक विशिष्ट 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) मॉड्यूल के लिंक होते हैं जो संबंधित विषयों को कवर करते हैं। ## शुरुआत करना -### 🎯 AI में नए हैं? यहाँ से शुरू करें! +### 🎯 AI में नए हैं? यहां से शुरू करें! -यदि आप AI में बिलकुल नए हैं और त्वरित, हाथों-हाथ उदाहरण चाहते हैं, तो हमारे [**शिक्षार्थी-अनुकूल उदाहरण**](./examples/README.md) देखें! इनमें शामिल हैं: +यदि आप AI में बिलकुल नए हैं और त्वरित, व्यावहारिक उदाहरण चाहते हैं, तो हमारे [**शुरुआती-अनुकूल उदाहरण**](./examples/README.md) देखें! इनमें शामिल हैं: -- 🌟 **हैलो AI वर्ल्ड** - आपका पहला AI प्रोग्राम (पैटर्न मान्यता) -- 🧠 **सरल न्यूरल नेटवर्क** - खरोंच से एक न्यूरल नेटवर्क बनाएं +- 🌟 **हैलो AI वर्ल्ड** - आपका पहला AI प्रोग्राम (पैटर्न रिकग्निशन) +- 🧠 **सरल न्यूरल नेटवर्क** - ज़मीन से न्यूरल नेटवर्क बनाएं +- 🖼️ **छवि वर्गीकर्ता** - विस्तृत टिप्पणियों के साथ छवियों को वर्गीकृत करें +- 💬 **पाठ भावना विश्लेषण** - सकारात्मक/नकारात्मक पाठ विश्लेषण करें -- 🖼️ **इमेज क्लासिफायर** - विस्तार से टिप्पणियों के साथ छवियों को वर्गीकृत करें -- 💬 **टेक्स्ट सेंटिमेंट** - सकारात्मक/नकारात्मक पाठ का विश्लेषण करें - -ये उदाहरण आपको पूरी पाठ्यक्रम में जाने से पहले AI अवधारणाओं को समझने में मदद करने के लिए डिज़ाइन किए गए हैं। +ये उदाहरण आपको पूर्ण पाठ्यक्रम में प्रवेश करने से पहले AI अवधारणाओं को समझने में मदद करने के लिए डिज़ाइन किए गए हैं। ### 📚 पूर्ण पाठ्यक्रम सेटअप -- हमने आपके विकास पर्यावरण की स्थापना में मदद करने के लिए एक [सेटअप पाठ](./lessons/0-course-setup/setup.md) बनाया है। - शिक्षकों के लिए, हमने आपके लिए भी एक [पाठ्यक्रम सेटअप पाठ](./lessons/0-course-setup/for-teachers.md) बनाया है! -- कैसे [VSCode या Codespace में कोड चलाएं](./lessons/0-course-setup/how-to-run.md) +- हमने आपके विकास पर्यावरण को सेट अप करने में मदद के लिए [सेटअप पाठ](./lessons/0-course-setup/setup.md) बनाया है। +- शिक्षकों के लिए, हमने आपके लिए भी एक [पाठ्यक्रम सेटअप पाठ](./lessons/0-course-setup/for-teachers.md) बनाया है! +- VSCode या Codespace 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 पृष्ठ के शीर्ष-दाएँ कोने में "Fork" बटन पर क्लिक करें। +रिपॉजिटरी को फोर्क करें: इस पृष्ठ के ऊपर दाईं ओर "Fork" बटन पर क्लिक करें। -रिपॉजिटरी क्लोन करें: `git clone https://github.com/microsoft/AI-For-Beginners.git` +रिपॉजिटरी क्लोन करें: `git clone https://github.com/microsoft/AI-For-Beginners.git` -बाद में इसे आसानी से खोजने के लिए इस रिपॉजिटरी को स्टार (🌟) करना न भूलें। +इसे बाद में आसानी से खोजने के लिए इस रिपो को स्टार (🌟) करना न भूलें। ## अन्य शिक्षार्थियों से मिलें -हमारे [आधिकारिक AI डिस्कॉर्ड सर्वर](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) में जुड़ें ताकि आप इस कोर्स में शामिल अन्य शिक्षार्थियों से मिल सकें और नेटवर्किंग कर सकें और सहायता प्राप्त कर सकें। +इस कोर्स को ले रहे अन्य शिक्षार्थियों से मिलने और नेटवर्क बनाने के लिए हमारे [आधिकारिक AI डिस्कॉर्ड सर्वर](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum) में जुड़ें और सहायता प्राप्त करें। -यदि आपके पास उत्पाद प्रतिक्रिया या प्रश्न हैं तो हमारे [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) पर जाएं। +यदि आपके पास प्रोडक्ट फीडबैक या प्रश्न हैं तो हमारे [Azure AI Foundry Developer Forum](https://aka.ms/foundry/forum) पर जाएँ। -## क्विज़ +## प्रश्नोत्तरी -> **क्विज़ के बारे में एक नोट**: सभी क्विज़ etc\quiz-app फ़ोल्डर के Quiz-app में संलग्न हैं, या [यहाँ ऑनलाइन](https://ff-quizzes.netlify.app/) उपलब्ध हैं। ये पाठों में लिंक किए गए हैं। क्विज़ ऐप को स्थानीय रूप से चलाया जा सकता है या Azure पर तैनात किया जा सकता है; `quiz-app` फ़ोल्डर में दिए निर्देशों का पालन करें। इन्हें धीरे-धीरे स्थानीयकृत किया जा रहा है। +> **प्रश्नोत्तरी के बारे में एक नोट**: सभी प्रश्नोत्तरी Quiz-app फोल्डर etc\quiz-app में रखी गई हैं, या [ऑनलाइन यहां](https://ff-quizzes.netlify.app/) उपलब्ध हैं। इन्हें पाठों के भीतर लिंक किया गया है। क्विज ऐप स्थानीय रूप से चलाया जा सकता है या Azure पर तैनात किया जा सकता है; निर्देशों के लिए `quiz-app` फोल्डर देखें। इन्हें क्रमिक रूप से स्थानीयकृत किया जा रहा है। -## सहायता आवश्यक है +## सहायता की आवश्यकता -क्या आपके पास सुझाव हैं या आपने वर्तनी या कोड त्रुटियां पाई हैं? एक समस्या उठाएं या पुल अनुरोध बनाएं। +क्या आपके पास सुझाव हैं या आपने वर्तनी या कोड में त्रुटियां पाई हैं? एक इश्यू उठाएं या पुल रिक्वेस्ट बनाएं। ## विशेष धन्यवाद -* **✍️ मुख्य लेखक:** [डिमित्रि सोश्निकोव](http://soshnikov.com), PhD -* **🔥 संपादक:** [जेन लूपर](https://twitter.com/jenlooper), PhD -* **🎨 स्केचनोट चित्रकार:** [टोमोमी इमुरा](https://twitter.com/girlie_mac) -* **✅ क्विज़ निर्माता:** [लतीफा बेलो](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/) -* **🙏 मुख्य योगदानकर्ता:** [एवगेनी पिशचिक](https://github.com/Pe4enIks) +* **✍️ मुख्य लेखक:** [Dmitry Soshnikov](http://soshnikov.com), PhD +* **🔥 संपादक:** [Jen Looper](https://twitter.com/jenlooper), PhD +* **🎨 स्केचनोट चित्रकार:** [Tomomi Imura](https://twitter.com/girlie_mac) +* **✅ प्रश्नोत्तरी निर्माता:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/) +* **🙏 कोर योगदानकर्ता:** [Evgenii Pishchik](https://github.com/Pe4enIks) ## अन्य पाठ्यक्रम -हमारी टीम अन्य पाठ्यक्रम तैयार करती है! देखें: +हमारी टीम अन्य पाठ्यक्रम भी बनाती है! देखें: ### LangChain @@ -181,7 +191,7 @@ _क्लाउड में AI_ विषयों के लिए एक स --- -### जनरेटिव AI सीरीज +### Generative AI Series [![Generative AI for Beginners](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) [![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) [![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) @@ -189,7 +199,7 @@ _क्लाउड में AI_ विषयों के लिए एक स --- -### मूल सीखना +### Core Learning [![ML for Beginners](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) [![Data Science for Beginners](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) [![AI for Beginners](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) @@ -200,25 +210,25 @@ _क्लाउड में AI_ विषयों के लिए एक स --- -### Copilot सीरीज +### Copilot Series [![Copilot for AI Paired Programming](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) [![Copilot for C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) [![Copilot Adventure](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) -## मदद लेना +## सहायता प्राप्त करें -यदि आप अटक गए हैं या AI ऐप बनाने के बारे में कोई प्रश्न हैं। MCP के बारे में चर्चा में साथी शिक्षार्थियों और अनुभवी डेवलपर्स से जुड़ें। यह एक सहायक समुदाय है जहाँ प्रश्न स्वागत योग्य हैं और ज्ञान स्वतंत्र रूप से साझा किया जाता है। +यदि आप अटक गए हैं या AI ऐप बनाने में कोई प्रश्न है, तो MCP पर चर्चा में अन्य शिक्षार्थियों और अनुभवी डेवलपर्स से जुड़ें। यह एक सहायक समुदाय है जहाँ प्रश्न पूछे जा सकते हैं और ज्ञान स्वतंत्र रूप से साझा किया जाता है। -[![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) +[![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -यदि आपके पास उत्पाद प्रतिक्रिया या निर्माण के दौरान त्रुटियां हैं तो जाएँ: +यदि निर्माण के दौरान आपके पास प्रोडक्ट फीडबैक या त्रुटियां हैं तो यहां जाएं: [![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) --- -**अस्वीकरण**: -यह दस्तावेज़ एआई अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) का उपयोग करके अनुवादित किया गया है। हम सटीकता के लिए प्रयासरत हैं, लेकिन कृपया ध्यान रखें कि स्वचालित अनुवादों में त्रुटियाँ या अशुद्धियां हो सकती हैं। मूल दस्तावेज़ अपनी स्थानीय भाषा में अधिकृत स्रोत माना जाना चाहिए। महत्वपूर्ण जानकारी के लिए, पेशेवर मानवीय अनुवाद की अनुशंसा की जाती है। इस अनुवाद के उपयोग से उत्पन्न किसी भी गलतफहमी या गलत व्याख्या के लिए हम उत्तरदायी नहीं हैं। +**अस्वीकरण**: +इस दस्तावेज़ का अनुवाद AI अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) का उपयोग करके किया गया है। यद्यपि हम सटीकता के लिए प्रयासरत हैं, कृपया ध्यान दें कि स्वचालित अनुवाद में त्रुटियाँ या असंगतियाँ हो सकती हैं। मूल दस्तावेज़, जिसे इसकी मूल भाषा में प्रस्तुत किया गया है, उसे अधिकृत स्रोत माना जाना चाहिए। महत्वपूर्ण जानकारी के लिए, पेशेवर मानव अनुवाद की सलाह दी जाती है। इस अनुवाद के उपयोग से उत्पन्न किसी भी गलतफहमी या गलत व्याख्या के लिए हम उत्तरदायी नहीं हैं। \ No newline at end of file diff --git a/translations/hi/lessons/2-Symbolic/MSConceptGraph.ipynb b/translations/hi/lessons/2-Symbolic/MSConceptGraph.ipynb index b44ccdf6..bb724a78 100644 --- a/translations/hi/lessons/2-Symbolic/MSConceptGraph.ipynb +++ b/translations/hi/lessons/2-Symbolic/MSConceptGraph.ipynb @@ -1,538 +1,532 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "collapsed": true - }, - "source": [ - "## Microsoft Concept Graph - यह API अब उपलब्ध नहीं है, लेकिन कृपया नोटबुक देखें ताकि अवधारणा को समझा जा सके\n", - "\n", - "[Microsoft Concept Graph](https://concept.research.microsoft.com/) इंटरनेट से प्राप्त शब्दों का एक बड़ा वर्गीकरण है, जिसमें अवधारणाओं के बीच `is-a` संबंध होते हैं।\n", - "\n", - "Context Graph दो रूपों में उपलब्ध है:\n", - " * डाउनलोड के लिए बड़ा टेक्स्ट फ़ाइल\n", - " * REST API\n", - "\n", - "सांख्यिकी:\n", - " * 5401933 अद्वितीय अवधारणाएँ,\n", - " * 12551613 अद्वितीय उदाहरण\n", - " * 87603947 `is-a` संबंध\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## वेब सेवा का उपयोग करना\n", - "\n", - "वेब सेवा विभिन्न समूहों में किसी अवधारणा के संबंधित होने की संभावना का अनुमान लगाने के लिए अलग-अलग कॉल प्रदान करती है। अधिक जानकारी [यहां](https://concept.research.microsoft.com/Home/Api) उपलब्ध है। कॉल करने के लिए यहां एक नमूना URL है: `https://api.conceptnet.io/query?start=/c/en/microsoft&rel=/r/IsA&limit=10`\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "trusted": true - }, - "outputs": [], - "source": [ - "import urllib\n", - "import json\n", - "\n", - "def http(x):\n", - " response = urllib.request.urlopen(x)\n", - " data = response.read()\n", - " return data.decode('utf-8')\n", - "\n", - "def query(x):\n", - " concept = x.lower().replace(' ', '_')\n", - " url = \"https://api.conceptnet.io/query?start=/c/en/{}&rel=/r/IsA&limit=10\".format(\n", - " urllib.parse.quote(concept))\n", - " try:\n", - " result = json.loads(http(url))\n", - " except Exception:\n", - " return {}\n", - " edges = result.get('edges', [])\n", - " if not edges:\n", - " return {}\n", - " total_weight = sum(edge['weight'] for edge in edges)\n", - " if total_weight == 0:\n", - " return {}\n", - " return {edge['end']['label']: edge['weight'] / total_weight for edge in edges}\n", - "\n", - "query('microsoft')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "चलो समाचार शीर्षकों को मुख्य अवधारणाओं के तहत वर्गीकृत करने की कोशिश करते हैं। समाचार शीर्षक प्राप्त करने के लिए, हम [NewsApi.org](http://newsapi.org) सेवा का उपयोग करेंगे। इस सेवा का उपयोग करने के लिए आपको अपना API कुंजी प्राप्त करनी होगी - वेबसाइट पर जाएं और मुफ्त डेवलपर योजना के लिए पंजीकरण करें।\n" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": { - "trusted": true - }, - "outputs": [], - "source": [ - "newsapi_key = ''\n", - "def get_news(country='us'):\n", - " res = json.loads(http(\"https://newsapi.org/v2/top-headlines?country={0}&apiKey={1}\".format(country,newsapi_key)))\n", - " return res['articles']\n", - "\n", - "all_titles = [x['title'] for x in get_news('us')+get_news('gb')]" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['Covid-19 Live Updates: Vaccines and Boosters News - The New York Times',\n", - " 'Ukrainians Flee Mariupol as Russian Forces Push to Take Port City - The Wall Street Journal',\n", - " 'Bond Yields Jump, Stock Futures Rise After Powell Says Fed Is Ready to Be More Aggressive - The Wall Street Journal',\n", - " 'Putin critic Alexei Navalny found guilty by Russian court - New York Post ',\n", - " \"Supreme Court nominee Ketanji Brown Jackson will face questions at confirmation hearing's second day - CNN\",\n", - " '2 teachers killed at Swedish high school, student arrested - ABC News',\n", - " 'Clues to Covid-19’s Next Moves Come From Sewers - The Wall Street Journal',\n", - " 'Republicans to roll dice by grilling Jackson over child-pornography sentencing decisions | TheHill - The Hill',\n", - " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", - " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", - " \"US stocks whipsawed overnight after Fed Chair Powell's remarks - Fox Business\",\n", - " \"'We've learned absolutely nothing': Tests could again be in short supply if Covid surges - POLITICO\",\n", - " \"Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\",\n", - " 'China searches for victims, flight recorders after first plane crash in 12 years - Reuters',\n", - " 'Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters',\n", - " 'Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español',\n", - " 'Powers Remain and Threats Lurk as Women’s Sweet 16 Is Set - The New York Times',\n", - " 'Webb Space Telescope Begins Multi-Instrument Alignment - SciTechDaily',\n", - " \"UConn vs UCF - NCAA women's tournament second-round highlights - March Madness\",\n", - " 'Bucking Republican Trend, Indiana Governor Vetoes Transgender Sports Bill - The New York Times',\n", - " \"Maggie Fox dead: Coronation Street and Shameless actress dies after 'sudden accident' - Mirror Online - The Mirror\",\n", - " 'China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent',\n", - " 'Daniel Morgan murder: damning report condemns Met police - The Guardian',\n", - " 'What to expect from Rishi Sunak’s Spring Statement - BBC.com',\n", - " 'UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian',\n", - " \"Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\",\n", - " 'Brass Eye’s outtakes show the brutal TV comedy was the tip of an iceberg - The Guardian',\n", - " \"Vladimir Putin threatens civilians to break Mariupol's spirit - The Times\",\n", - " 'Shell U-turn on Cambo oilfield would threaten green targets, say campaigners - The Guardian',\n", - " 'St Helens dog attack: Girl aged 17 months killed at home - BBC',\n", - " \"PlayStation to buy 'Assassin's Creed' veteran Jade Raymond's Haven Studios - NME\",\n", - " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", - " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", - " 'Nintendo Switch finally has folders • Eurogamer.net - Eurogamer.net',\n", - " 'FA to “find a solution” as Liverpool fan group blasts “shambolic” Wembley travel - This Is Anfield',\n", - " 'Manchester United transfer news LIVE Erik ten Hag latest and Man Utd manager updates - Manchester Evening News',\n", - " 'Inflation raises cost of UK government borrowing in February; crude oil up again – business live - The Guardian',\n", - " 'Alexei Navalny: Kremlin critic found guilty of large-scale fraud and contempt of court by Russian court - Sky News',\n", - " \"UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\",\n", - " 'Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian']" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "all_titles" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "सबसे पहले, हम समाचार शीर्षकों से संज्ञा निकालने में सक्षम होना चाहते हैं। हम इसके लिए `TextBlob` लाइब्रेरी का उपयोग करेंगे, जो इस तरह के सामान्य NLP कार्यों को बहुत सरल बनाती है।\n" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: textblob in c:\\winapp\\miniconda3\\lib\\site-packages (0.17.1)\n", - "Requirement already satisfied: nltk>=3.1 in c:\\winapp\\miniconda3\\lib\\site-packages (from textblob) (3.5)\n", - "Requirement already satisfied: joblib in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (1.0.1)\n", - "Requirement already satisfied: regex in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (2021.11.10)\n", - "Requirement already satisfied: tqdm in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (4.61.2)\n", - "Requirement already satisfied: click in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (8.0.3)\n", - "Requirement already satisfied: colorama in c:\\winapp\\miniconda3\\lib\\site-packages (from click->nltk>=3.1->textblob) (0.4.4)\n", - "Finished.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[nltk_data] Downloading package brown to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package brown is already up-to-date!\n", - "[nltk_data] Downloading package punkt to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package punkt is already up-to-date!\n", - "[nltk_data] Downloading package wordnet to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package wordnet is already up-to-date!\n", - "[nltk_data] Downloading package averaged_perceptron_tagger to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package averaged_perceptron_tagger is already up-to-\n", - "[nltk_data] date!\n", - "[nltk_data] Downloading package conll2000 to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package conll2000 is already up-to-date!\n", - "[nltk_data] Downloading package movie_reviews to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package movie_reviews is already up-to-date!\n" - ] - } - ], - "source": [ - "import sys\n", - "!{sys.executable} -m pip install textblob\n", - "!{sys.executable} -m textblob.download_corpora\n", - "from textblob import TextBlob" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "{'covid-19 live updates': 1,\n", - " 'vaccines': 1,\n", - " 'boosters': 1,\n", - " 'york': 4,\n", - " 'ukrainians flee mariupol': 1,\n", - " 'forces push': 1,\n", - " 'port city': 1,\n", - " 'wall street journal': 3,\n", - " 'bond yields': 1,\n", - " 'futures rise': 1,\n", - " 'powell says fed': 1,\n", - " 'ready': 1,\n", - " 'be': 1,\n", - " 'aggressive': 1,\n", - " 'putin': 3,\n", - " 'alexei navalny': 2,\n", - " 'russian': 2,\n", - " 'supreme court nominee': 1,\n", - " 'ketanji brown jackson': 1,\n", - " \"confirmation hearing 's\": 1,\n", - " 'cnn': 1,\n", - " 'swedish': 1,\n", - " 'high school': 1,\n", - " 'abc': 1,\n", - " 'clues': 1,\n", - " 'covid-19': 1,\n", - " '’ s': 2,\n", - " 'moves': 1,\n", - " 'sewers': 1,\n", - " 'roll dice': 1,\n", - " 'jackson': 1,\n", - " 'decisions |': 1,\n", - " 'thehill': 1,\n", - " 'clear': 2,\n", - " 'chemical weapons': 2,\n", - " 'ukraine': 3,\n", - " 'claims president': 2,\n", - " 'biden': 2,\n", - " 'nasa': 2,\n", - " 'solar system': 2,\n", - " 'daily mail': 3,\n", - " 'us stocks': 1,\n", - " 'fed chair powell': 1,\n", - " \"'s remarks\": 1,\n", - " 'fox': 1,\n", - " \"'we 've\": 1,\n", - " 'tests': 1,\n", - " 'covid': 1,\n", - " 'politico': 1,\n", - " 'duchess': 1,\n", - " 'cambridge': 1,\n", - " 'swaps khaki jungle gear': 1,\n", - " 'vampire': 1,\n", - " 'wife': 1,\n", - " 'belize': 1,\n", - " 'china': 2,\n", - " 'flight recorders': 1,\n", - " 'plane crash': 1,\n", - " 'reuters': 2,\n", - " 'russian oligarch': 1,\n", - " 'abramovich': 1,\n", - " 'live': 1,\n", - " 'russia': 2,\n", - " 'stops talks': 1,\n", - " 'japan': 1,\n", - " 'español': 1,\n", - " 'powers remain': 1,\n", - " 'threats lurk': 1,\n", - " 'set': 1,\n", - " 'webb': 1,\n", - " 'telescope begins multi-instrument alignment': 1,\n", - " 'scitechdaily': 1,\n", - " 'uconn': 1,\n", - " 'ucf': 1,\n", - " 'ncaa': 1,\n", - " \"women 's tournament second-round highlights\": 1,\n", - " 'march madness': 1,\n", - " 'bucking republican trend': 1,\n", - " 'indiana': 1,\n", - " 'vetoes transgender': 1,\n", - " 'bill': 1,\n", - " 'maggie fox': 1,\n", - " 'coronation': 1,\n", - " 'shameless': 1,\n", - " \"'sudden accident\": 1,\n", - " 'mirror online': 1,\n", - " 'mirror': 2,\n", - " 'plane crash –': 1,\n", - " 'search': 1,\n", - " 'moment flight': 1,\n", - " 'daniel morgan': 1,\n", - " 'report condemns': 1,\n", - " 'met': 1,\n", - " 'guardian': 6,\n", - " 'rishi sunak': 1,\n", - " '’ s spring': 1,\n", - " 'statement': 1,\n", - " 'bbc.com': 1,\n", - " 'uk': 3,\n", - " 'ireland': 1,\n", - " 'euro': 1,\n", - " 'vladimir putin': 2,\n", - " \"'s 'lover\": 1,\n", - " 'brass eye': 1,\n", - " '’ s outtakes': 1,\n", - " 'brutal tv comedy': 1,\n", - " 'threatens civilians': 1,\n", - " 'mariupol': 1,\n", - " \"'s spirit\": 1,\n", - " 'shell u-turn': 1,\n", - " 'cambo': 1,\n", - " 'green targets': 1,\n", - " 'st helens': 1,\n", - " 'dog attack': 1,\n", - " 'girl': 1,\n", - " 'bbc': 1,\n", - " 'playstation': 1,\n", - " \"'assassin 's\": 1,\n", - " 'creed': 1,\n", - " 'jade raymond': 1,\n", - " 'haven studios': 1,\n", - " 'nme': 1,\n", - " 'nintendo switch': 1,\n", - " 'folders •': 1,\n", - " 'eurogamer.net': 2,\n", - " 'fa': 1,\n", - " 'solution ”': 1,\n", - " 'liverpool': 1,\n", - " 'fan group blasts “ shambolic ”': 1,\n", - " 'wembley': 1,\n", - " 'anfield': 1,\n", - " 'manchester': 1,\n", - " 'live erik': 1,\n", - " 'hag': 1,\n", - " 'utd': 1,\n", - " 'manager updates': 1,\n", - " 'manchester evening': 1,\n", - " 'inflation': 1,\n", - " 'government borrowing': 1,\n", - " 'february': 1,\n", - " 'crude oil': 1,\n", - " '– business': 1,\n", - " 'kremlin': 1,\n", - " 'large-scale fraud': 1,\n", - " 'sky': 1,\n", - " 'natural gas': 1,\n", - " 'gazprom': 1,\n", - " 'retail unit': 1,\n", - " 'insider': 1,\n", - " 'zaghari-ratcliffe': 1,\n", - " 'hunt': 1,\n", - " 'iran': 1,\n", - " 'debt payment': 1}" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "w = {}\n", - "for x in all_titles:\n", - " for n in TextBlob(x).noun_phrases:\n", - " if n in w:\n", - " w[n].append(x)\n", - " else:\n", - " w[n]=[x]\n", - "{ x:len(w[x]) for x in w.keys()}" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "हम देख सकते हैं कि संज्ञाएं हमें बड़े थीमेटिक समूह नहीं देती हैं। आइए संज्ञाओं को अवधारणा ग्राफ से प्राप्त अधिक सामान्य शब्दों से बदलें। इसमें कुछ समय लगेगा, क्योंकि हम प्रत्येक संज्ञा वाक्यांश के लिए REST कॉल कर रहे हैं।\n" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": { - "trusted": true - }, - "outputs": [], - "source": [ - "w = {}\n", - "for x in all_titles:\n", - " for noun in TextBlob(x).noun_phrases:\n", - " terms = query(noun)\n", - " for term in [u for u in terms.keys() if terms[u]>0.1]:\n", - " if term in w:\n", - " w[term].append(x)\n", - " else:\n", - " w[term]=[x]" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "{'city': 9,\n", - " 'brand': 4,\n", - " 'place': 9,\n", - " 'town': 4,\n", - " 'factor': 4,\n", - " 'film': 4,\n", - " 'nation': 11,\n", - " 'state': 5,\n", - " 'person': 4,\n", - " 'organization': 5,\n", - " 'publication': 10,\n", - " 'market': 5,\n", - " 'economy': 4,\n", - " 'company': 6,\n", - " 'newspaper': 6,\n", - " 'relationship': 6}" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "{ x:len(w[x]) for x in w.keys() if len(w[x])>3}" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "ECONOMY:\n", - "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", - "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", - "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", - "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", - "\n", - "NATION:\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", - "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", - "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", - "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", - "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", - "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", - "UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian\n", - "Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", - "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", - "Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian\n", - "\n", - "PERSON:\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", - "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", - "Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n" - ] - } - ], - "source": [ - "print('\\nECONOMY:\\n'+'\\n'.join(w['economy']))\n", - "print('\\nNATION:\\n'+'\\n'.join(w['nation']))\n", - "print('\\nPERSON:\\n'+'\\n'.join(w['person']))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n---\n\n**अस्वीकरण**: \nयह 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 अनुवाद में त्रुटियां या अशुद्धियां हो सकती हैं। मूल दस्तावेज़ को उसकी मूल भाषा में 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।\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3.7.4 64-bit (conda)", - "metadata": { - "interpreter": { - "hash": "86193a1ab0ba47eac1c69c1756090baa3b420b3eea7d4aafab8b85f8b312f0c5" - } - }, - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.5" - }, - "coopTranslator": { - "original_hash": "7b3f1fc049371bcf8649ac9fefdf0413", - "translation_date": "2025-10-03T18:52:37+00:00", - "source_file": "lessons/2-Symbolic/MSConceptGraph.ipynb", - "language_code": "hi" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "## कॉन्सेप्ट ग्राफ उपयोग करते हुए ConceptNet\n", + "\n", + "> **नोट:** मूल [Microsoft Concept Graph](https://concept.research.microsoft.com/) API अब उपलब्ध नहीं है। इस नोटबुक को [ConceptNet](https://conceptnet.io/) का उपयोग करने के लिए अपडेट किया गया है, जो कि एक मुफ्त उपलब्ध ओपन नॉलेज ग्राफ है जिसमें अवधारणाओं के बीच समान `is-a` संबंध होते हैं।\n", + "\n", + "[ConceptNet](https://conceptnet.io/) अवधारणाओं का एक बड़ा सेमांटिक नेटवर्क है जिसमें `IsA`, `PartOf`, `UsedFor`, और अन्य संबंध शामिल हैं। यह उपलब्ध है:\n", + " * एक डाउनलोड करने योग्य डेटा फाइल के रूप में\n", + " * एक REST API के रूप में (कोई API कुंजी आवश्यक नहीं)\n", + "\n", + "ConceptNet सांख्यिकी:\n", + " * 8 मिलियन से अधिक नोड्स\n", + " * 83 भाषाओं में 21+ मिलियन एजेस\n" + ] }, - "nbformat": 4, - "nbformat_minor": 2 + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## ConceptNet वेब सेवा का उपयोग करना\n", + "\n", + "[ConceptNet](https://conceptnet.io/) अवधारणाओं के बीच `is-a` (IsA) संबंधों का पता लगाने के लिए एक REST API प्रदान करता है। किसी API कुंजी की आवश्यकता नहीं है। \n", + "यहां कॉल करने के लिए नमूना URL है: `https://api.conceptnet.io/query?start=/c/en/microsoft&rel=/r/IsA&limit=10`\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "import urllib\n", + "import json\n", + "\n", + "def http(x):\n", + " response = urllib.request.urlopen(x)\n", + " data = response.read()\n", + " return data.decode('utf-8')\n", + "\n", + "def query(x):\n", + " concept = x.lower().replace(' ', '_')\n", + " url = \"https://api.conceptnet.io/query?start=/c/en/{}&rel=/r/IsA&limit=10\".format(\n", + " urllib.parse.quote(concept))\n", + " try:\n", + " result = json.loads(http(url))\n", + " except Exception:\n", + " return {}\n", + " edges = result.get('edges', [])\n", + " if not edges:\n", + " return {}\n", + " total_weight = sum(edge['weight'] for edge in edges)\n", + " if total_weight == 0:\n", + " return {}\n", + " return {edge['end']['label']: edge['weight'] / total_weight for edge in edges}\n", + "\n", + "query('microsoft')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "आइए समाचार शीर्षकों को माता-पिता अवधारणाओं के अनुसार वर्गीकृत करने का प्रयास करें। समाचार शीर्षक प्राप्त करने के लिए, हम [NewsApi.org](http://newsapi.org) सेवा का उपयोग करेंगे। सेवा का उपयोग करने के लिए आपको अपनी खुद की API कुंजी प्राप्त करनी होगी - वेबसाइट पर जाएं और मुफ्त डेवलपर योजना के लिए पंजीकरण करें।\n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "newsapi_key = ''\n", + "def get_news(country='us'):\n", + " res = json.loads(http(\"https://newsapi.org/v2/top-headlines?country={0}&apiKey={1}\".format(country,newsapi_key)))\n", + " return res['articles']\n", + "\n", + "all_titles = [x['title'] for x in get_news('us')+get_news('gb')]" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Covid-19 Live Updates: Vaccines and Boosters News - The New York Times',\n", + " 'Ukrainians Flee Mariupol as Russian Forces Push to Take Port City - The Wall Street Journal',\n", + " 'Bond Yields Jump, Stock Futures Rise After Powell Says Fed Is Ready to Be More Aggressive - The Wall Street Journal',\n", + " 'Putin critic Alexei Navalny found guilty by Russian court - New York Post ',\n", + " \"Supreme Court nominee Ketanji Brown Jackson will face questions at confirmation hearing's second day - CNN\",\n", + " '2 teachers killed at Swedish high school, student arrested - ABC News',\n", + " 'Clues to Covid-19’s Next Moves Come From Sewers - The Wall Street Journal',\n", + " 'Republicans to roll dice by grilling Jackson over child-pornography sentencing decisions | TheHill - The Hill',\n", + " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", + " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", + " \"US stocks whipsawed overnight after Fed Chair Powell's remarks - Fox Business\",\n", + " \"'We've learned absolutely nothing': Tests could again be in short supply if Covid surges - POLITICO\",\n", + " \"Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\",\n", + " 'China searches for victims, flight recorders after first plane crash in 12 years - Reuters',\n", + " 'Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters',\n", + " 'Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español',\n", + " 'Powers Remain and Threats Lurk as Women’s Sweet 16 Is Set - The New York Times',\n", + " 'Webb Space Telescope Begins Multi-Instrument Alignment - SciTechDaily',\n", + " \"UConn vs UCF - NCAA women's tournament second-round highlights - March Madness\",\n", + " 'Bucking Republican Trend, Indiana Governor Vetoes Transgender Sports Bill - The New York Times',\n", + " \"Maggie Fox dead: Coronation Street and Shameless actress dies after 'sudden accident' - Mirror Online - The Mirror\",\n", + " 'China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent',\n", + " 'Daniel Morgan murder: damning report condemns Met police - The Guardian',\n", + " 'What to expect from Rishi Sunak’s Spring Statement - BBC.com',\n", + " 'UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian',\n", + " \"Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\",\n", + " 'Brass Eye’s outtakes show the brutal TV comedy was the tip of an iceberg - The Guardian',\n", + " \"Vladimir Putin threatens civilians to break Mariupol's spirit - The Times\",\n", + " 'Shell U-turn on Cambo oilfield would threaten green targets, say campaigners - The Guardian',\n", + " 'St Helens dog attack: Girl aged 17 months killed at home - BBC',\n", + " \"PlayStation to buy 'Assassin's Creed' veteran Jade Raymond's Haven Studios - NME\",\n", + " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", + " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", + " 'Nintendo Switch finally has folders • Eurogamer.net - Eurogamer.net',\n", + " 'FA to “find a solution” as Liverpool fan group blasts “shambolic” Wembley travel - This Is Anfield',\n", + " 'Manchester United transfer news LIVE Erik ten Hag latest and Man Utd manager updates - Manchester Evening News',\n", + " 'Inflation raises cost of UK government borrowing in February; crude oil up again – business live - The Guardian',\n", + " 'Alexei Navalny: Kremlin critic found guilty of large-scale fraud and contempt of court by Russian court - Sky News',\n", + " \"UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\",\n", + " 'Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian']" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "all_titles" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "सबसे पहले, हम समाचार शीर्षकों से संज्ञाएँ निकालने में सक्षम होना चाहते हैं। इसके लिए हम `TextBlob` लाइब्रेरी का उपयोग करेंगे, जो इस तरह के कई सामान्य NLP कार्यों को सरल बनाती है।\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: textblob in c:\\winapp\\miniconda3\\lib\\site-packages (0.17.1)\n", + "Requirement already satisfied: nltk>=3.1 in c:\\winapp\\miniconda3\\lib\\site-packages (from textblob) (3.5)\n", + "Requirement already satisfied: joblib in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (1.0.1)\n", + "Requirement already satisfied: regex in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (2021.11.10)\n", + "Requirement already satisfied: tqdm in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (4.61.2)\n", + "Requirement already satisfied: click in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (8.0.3)\n", + "Requirement already satisfied: colorama in c:\\winapp\\miniconda3\\lib\\site-packages (from click->nltk>=3.1->textblob) (0.4.4)\n", + "Finished.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[nltk_data] Downloading package brown to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package brown is already up-to-date!\n", + "[nltk_data] Downloading package punkt to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package punkt is already up-to-date!\n", + "[nltk_data] Downloading package wordnet to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package averaged_perceptron_tagger to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package averaged_perceptron_tagger is already up-to-\n", + "[nltk_data] date!\n", + "[nltk_data] Downloading package conll2000 to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package conll2000 is already up-to-date!\n", + "[nltk_data] Downloading package movie_reviews to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package movie_reviews is already up-to-date!\n" + ] + } + ], + "source": [ + "import sys\n", + "!{sys.executable} -m pip install textblob\n", + "!{sys.executable} -m textblob.download_corpora\n", + "from textblob import TextBlob" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'covid-19 live updates': 1,\n", + " 'vaccines': 1,\n", + " 'boosters': 1,\n", + " 'york': 4,\n", + " 'ukrainians flee mariupol': 1,\n", + " 'forces push': 1,\n", + " 'port city': 1,\n", + " 'wall street journal': 3,\n", + " 'bond yields': 1,\n", + " 'futures rise': 1,\n", + " 'powell says fed': 1,\n", + " 'ready': 1,\n", + " 'be': 1,\n", + " 'aggressive': 1,\n", + " 'putin': 3,\n", + " 'alexei navalny': 2,\n", + " 'russian': 2,\n", + " 'supreme court nominee': 1,\n", + " 'ketanji brown jackson': 1,\n", + " \"confirmation hearing 's\": 1,\n", + " 'cnn': 1,\n", + " 'swedish': 1,\n", + " 'high school': 1,\n", + " 'abc': 1,\n", + " 'clues': 1,\n", + " 'covid-19': 1,\n", + " '’ s': 2,\n", + " 'moves': 1,\n", + " 'sewers': 1,\n", + " 'roll dice': 1,\n", + " 'jackson': 1,\n", + " 'decisions |': 1,\n", + " 'thehill': 1,\n", + " 'clear': 2,\n", + " 'chemical weapons': 2,\n", + " 'ukraine': 3,\n", + " 'claims president': 2,\n", + " 'biden': 2,\n", + " 'nasa': 2,\n", + " 'solar system': 2,\n", + " 'daily mail': 3,\n", + " 'us stocks': 1,\n", + " 'fed chair powell': 1,\n", + " \"'s remarks\": 1,\n", + " 'fox': 1,\n", + " \"'we 've\": 1,\n", + " 'tests': 1,\n", + " 'covid': 1,\n", + " 'politico': 1,\n", + " 'duchess': 1,\n", + " 'cambridge': 1,\n", + " 'swaps khaki jungle gear': 1,\n", + " 'vampire': 1,\n", + " 'wife': 1,\n", + " 'belize': 1,\n", + " 'china': 2,\n", + " 'flight recorders': 1,\n", + " 'plane crash': 1,\n", + " 'reuters': 2,\n", + " 'russian oligarch': 1,\n", + " 'abramovich': 1,\n", + " 'live': 1,\n", + " 'russia': 2,\n", + " 'stops talks': 1,\n", + " 'japan': 1,\n", + " 'español': 1,\n", + " 'powers remain': 1,\n", + " 'threats lurk': 1,\n", + " 'set': 1,\n", + " 'webb': 1,\n", + " 'telescope begins multi-instrument alignment': 1,\n", + " 'scitechdaily': 1,\n", + " 'uconn': 1,\n", + " 'ucf': 1,\n", + " 'ncaa': 1,\n", + " \"women 's tournament second-round highlights\": 1,\n", + " 'march madness': 1,\n", + " 'bucking republican trend': 1,\n", + " 'indiana': 1,\n", + " 'vetoes transgender': 1,\n", + " 'bill': 1,\n", + " 'maggie fox': 1,\n", + " 'coronation': 1,\n", + " 'shameless': 1,\n", + " \"'sudden accident\": 1,\n", + " 'mirror online': 1,\n", + " 'mirror': 2,\n", + " 'plane crash –': 1,\n", + " 'search': 1,\n", + " 'moment flight': 1,\n", + " 'daniel morgan': 1,\n", + " 'report condemns': 1,\n", + " 'met': 1,\n", + " 'guardian': 6,\n", + " 'rishi sunak': 1,\n", + " '’ s spring': 1,\n", + " 'statement': 1,\n", + " 'bbc.com': 1,\n", + " 'uk': 3,\n", + " 'ireland': 1,\n", + " 'euro': 1,\n", + " 'vladimir putin': 2,\n", + " \"'s 'lover\": 1,\n", + " 'brass eye': 1,\n", + " '’ s outtakes': 1,\n", + " 'brutal tv comedy': 1,\n", + " 'threatens civilians': 1,\n", + " 'mariupol': 1,\n", + " \"'s spirit\": 1,\n", + " 'shell u-turn': 1,\n", + " 'cambo': 1,\n", + " 'green targets': 1,\n", + " 'st helens': 1,\n", + " 'dog attack': 1,\n", + " 'girl': 1,\n", + " 'bbc': 1,\n", + " 'playstation': 1,\n", + " \"'assassin 's\": 1,\n", + " 'creed': 1,\n", + " 'jade raymond': 1,\n", + " 'haven studios': 1,\n", + " 'nme': 1,\n", + " 'nintendo switch': 1,\n", + " 'folders •': 1,\n", + " 'eurogamer.net': 2,\n", + " 'fa': 1,\n", + " 'solution ”': 1,\n", + " 'liverpool': 1,\n", + " 'fan group blasts “ shambolic ”': 1,\n", + " 'wembley': 1,\n", + " 'anfield': 1,\n", + " 'manchester': 1,\n", + " 'live erik': 1,\n", + " 'hag': 1,\n", + " 'utd': 1,\n", + " 'manager updates': 1,\n", + " 'manchester evening': 1,\n", + " 'inflation': 1,\n", + " 'government borrowing': 1,\n", + " 'february': 1,\n", + " 'crude oil': 1,\n", + " '– business': 1,\n", + " 'kremlin': 1,\n", + " 'large-scale fraud': 1,\n", + " 'sky': 1,\n", + " 'natural gas': 1,\n", + " 'gazprom': 1,\n", + " 'retail unit': 1,\n", + " 'insider': 1,\n", + " 'zaghari-ratcliffe': 1,\n", + " 'hunt': 1,\n", + " 'iran': 1,\n", + " 'debt payment': 1}" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "w = {}\n", + "for x in all_titles:\n", + " for n in TextBlob(x).noun_phrases:\n", + " if n in w:\n", + " w[n].append(x)\n", + " else:\n", + " w[n]=[x]\n", + "{ x:len(w[x]) for x in w.keys()}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "हम देख सकते हैं कि संज्ञाएँ हमें बड़े थीमैटिक समूह नहीं देती हैं। आइए संज्ञाओं को अवधारणा ग्राफ़ से प्राप्त अधिक सामान्य शब्दों से प्रतिस्थापित करें। इसमें कुछ समय लगेगा, क्योंकि हम प्रत्येक संज्ञा वाक्यांश के लिए REST कॉल कर रहे हैं।\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "w = {}\n", + "for x in all_titles:\n", + " for noun in TextBlob(x).noun_phrases:\n", + " terms = query(noun)\n", + " for term in [u for u in terms.keys() if terms[u]>0.1]:\n", + " if term in w:\n", + " w[term].append(x)\n", + " else:\n", + " w[term]=[x]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'city': 9,\n", + " 'brand': 4,\n", + " 'place': 9,\n", + " 'town': 4,\n", + " 'factor': 4,\n", + " 'film': 4,\n", + " 'nation': 11,\n", + " 'state': 5,\n", + " 'person': 4,\n", + " 'organization': 5,\n", + " 'publication': 10,\n", + " 'market': 5,\n", + " 'economy': 4,\n", + " 'company': 6,\n", + " 'newspaper': 6,\n", + " 'relationship': 6}" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "{ x:len(w[x]) for x in w.keys() if len(w[x])>3}" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "ECONOMY:\n", + "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", + "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", + "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", + "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", + "\n", + "NATION:\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", + "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", + "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", + "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", + "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", + "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", + "UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian\n", + "Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", + "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", + "Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian\n", + "\n", + "PERSON:\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", + "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", + "Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n" + ] + } + ], + "source": [ + "print('\\nECONOMY:\\n'+'\\n'.join(w['economy']))\n", + "print('\\nNATION:\\n'+'\\n'.join(w['nation']))\n", + "print('\\nPERSON:\\n'+'\\n'.join(w['person']))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n\n\n**अस्वीकरण**:\nयह दस्तावेज़ AI अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) का उपयोग करके अनूदित किया गया है। यद्यपि हम सटीकता के लिए प्रयास करते हैं, कृपया ध्यान दें कि स्वचालित अनुवादों में त्रुटियां या अशुद्धताएं हो सकती हैं। मूल दस्तावेज़ को उसकी मूल भाषा में प्रामाणिक स्रोत माना जाना चाहिए। महत्वपूर्ण जानकारी के लिए, पेशेवर मानव अनुवाद की सलाह दी जाती है। इस अनुवाद के उपयोग से उत्पन्न किसी भी गलतफहमी या गलत व्याख्या के लिए हम उत्तरदायी नहीं हैं।\n\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.7.4 64-bit (conda)", + "metadata": { + "interpreter": { + "hash": "86193a1ab0ba47eac1c69c1756090baa3b420b3eea7d4aafab8b85f8b312f0c5" + } + }, + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 } \ No newline at end of file diff --git a/translations/ko/.co-op-translator.json b/translations/ko/.co-op-translator.json index 54b4c75c..e9187609 100644 --- a/translations/ko/.co-op-translator.json +++ b/translations/ko/.co-op-translator.json @@ -6,8 +6,8 @@ "language_code": "ko" }, "README.md": { - "original_hash": "75fe3383afc51eaa84b82ace619ffea7", - "translation_date": "2026-02-06T07:46:25+00:00", + "original_hash": "9eaca839b0b3f6d7f0a195fd33cebd30", + "translation_date": "2026-02-28T09:57:47+00:00", "source_file": "README.md", "language_code": "ko" }, @@ -89,6 +89,12 @@ "source_file": "lessons/1-Intro/assignment.md", "language_code": "ko" }, + "lessons/2-Symbolic/MSConceptGraph.ipynb": { + "original_hash": "e5690bbc6e5119a96a8172ec7261db67", + "translation_date": "2026-02-28T09:55:53+00:00", + "source_file": "lessons/2-Symbolic/MSConceptGraph.ipynb", + "language_code": "ko" + }, "lessons/2-Symbolic/README.md": { "original_hash": "f9f06b266b8b2bfc6b8792ff2bb1bea4", "translation_date": "2026-01-15T12:57:43+00:00", diff --git a/translations/ko/README.md b/translations/ko/README.md index c921d5a9..f3bb6e19 100644 --- a/translations/ko/README.md +++ b/translations/ko/README.md @@ -16,156 +16,164 @@ |![Sketchnote by @girlie_mac https://twitter.com/girlie_mac](https://github.com/microsoft/AI-For-Beginners/raw/main/lessons/sketchnotes/ai-overview.png)| |:---:| -| 초보자를 위한 AI - _[@girlie_mac](https://twitter.com/girlie_mac) 스케치노트_ | +| AI 초보자를 위한 커리큘럼 - _[@girlie_mac](https://twitter.com/girlie_mac) 제공 스케치노트_ | -12주, 24개 강의로 구성된 **인공지능**(AI) 세계를 탐험해보세요! 실습 강의, 퀴즈, 실험실이 포함되어 있습니다. 이 커리큘럼은 초보자 친화적이며 TensorFlow, PyTorch 같은 도구와 AI 윤리까지 다룹니다. +12주, 24개의 레슨으로 구성된 **인공지능**(AI) 세계를 탐험하세요! 이 커리큘럼에는 실습 강의, 퀴즈, 랩이 포함되어 있습니다. 초보자 친화적이며 TensorFlow와 PyTorch 같은 도구와 AI 윤리에 대해 다룹니다. +### 🌐 다중 언어 지원 -### 🌐 다국어 지원 - -#### GitHub Action을 통한 지원 (자동화 및 항상 최신 상태 유지) +#### GitHub Action을 통한 지원 (자동화 및 항상 최신 유지) -[Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](../zh-HK/README.md) | [Chinese (Traditional, Macau)](../zh-MO/README.md) | [Chinese (Traditional, Taiwan)](../zh-TW/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](./README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../pt-BR/README.md) | [Portuguese (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) +[Arabic](../ar/README.md) | [벵골어](../bn/README.md) | [불가리아어](../bg/README.md) | [버마어 (미얀마)](../my/README.md) | [중국어 (간체)](../zh-CN/README.md) | [중국어 (번체, 홍콩)](../zh-HK/README.md) | [중국어 (번체, 마카오)](../zh-MO/README.md) | [중국어 (번체, 대만)](../zh-TW/README.md) | [크로아티아어](../hr/README.md) | [체코어](../cs/README.md) | [덴마크어](../da/README.md) | [네덜란드어](../nl/README.md) | [에스토니아어](../et/README.md) | [핀란드어](../fi/README.md) | [프랑스어](../fr/README.md) | [독일어](../de/README.md) | [그리스어](../el/README.md) | [히브리어](../he/README.md) | [힌디어](../hi/README.md) | [헝가리어](../hu/README.md) | [인도네시아어](../id/README.md) | [이탈리아어](../it/README.md) | [일본어](../ja/README.md) | [칸나다어](../kn/README.md) | [한국어](./README.md) | [리투아니아어](../lt/README.md) | [말레이어](../ms/README.md) | [말라얄람어](../ml/README.md) | [마라티어](../mr/README.md) | [네팔어](../ne/README.md) | [나이지리아 피진어](../pcm/README.md) | [노르웨이어](../no/README.md) | [페르시아어 (파르시)](../fa/README.md) | [폴란드어](../pl/README.md) | [포르투갈어 (브라질)](../pt-BR/README.md) | [포르투갈어 (포르투갈)](../pt-PT/README.md) | [펀자브어 (구르무키)](../pa/README.md) | [루마니아어](../ro/README.md) | [러시아어](../ru/README.md) | [세르비아어 (키릴 문자)](../sr/README.md) | [슬로바키아어](../sk/README.md) | [슬로베니아어](../sl/README.md) | [스페인어](../es/README.md) | [스와힐리어](../sw/README.md) | [스웨덴어](../sv/README.md) | [따갈로그어 (필리핀어)](../tl/README.md) | [타밀어](../ta/README.md) | [텔루구어](../te/README.md) | [태국어](../th/README.md) | [터키어](../tr/README.md) | [우크라이나어](../uk/README.md) | [우르두어](../ur/README.md) | [베트남어](../vi/README.md) -> **로컬로 복제하는 것을 선호하시나요?** - -> 이 저장소는 50개 이상의 언어 번역을 포함하고 있으며, 이는 다운로드 크기가 상당히 커집니다. 번역 없이 복제하려면 sparse checkout을 사용하세요: +> **로컬 클론을 선호하시나요?** +> +> 이 저장소에는 50개 이상의 언어 번역본이 포함되어 있어 다운로드 크기가 크게 증가합니다. 번역 없이 클론하려면 sparse checkout을 사용하세요: +> +> **Bash / macOS / Linux:** > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git > cd AI-For-Beginners > git sparse-checkout set --no-cone '/*' '!translations' '!translated_images' > ``` -> 이렇게 하면 수업을 완료하는 데 필요한 모든 것을 훨씬 빠르게 다운로드할 수 있습니다. +> +> **CMD (Windows):** +> ```cmd +> git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git +> cd AI-For-Beginners +> git sparse-checkout set --no-cone "/*" "!translations" "!translated_images" +> ``` +> +> 이 방법으로 훨씬 빠른 다운로드로 코스 완료에 필요한 모든 것을 얻을 수 있습니다. -**추가 언어 번역 지원을 원하시면 [여기](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)에서 확인하세요** +**추가 언어 지원을 원하시면 [여기](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)에서 지원되는 언어 목록을 확인하세요.** -## 커뮤니티 참여하기 +## 커뮤니티에 참여하세요 [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -## 당신이 배우게 될 내용 +## 배우게 될 내용 -**[과정의 마인드맵](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** +**[코스 마인드맵](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** -이 커리큘럼에서 배우는 내용: +이 커리큘럼에서 배우게 될 내용: -* 지식 표현과 추론을 포함한 "고전적" 상징 접근법([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)) 등 인공지능에 대한 다양한 접근법. -* 현대 AI의 핵심인 **신경망**과 **딥러닝**. 두 가지 인기 프레임워크인 [TensorFlow](http://Tensorflow.org)와 [PyTorch](http://pytorch.org)의 코드로 개념 설명. -* 이미지와 텍스트와 작업하는 **신경망 아키텍처**. 최신 모델을 다루지만, 최신 최첨단 내용은 다소 부족할 수 있음. -* **유전 알고리즘**과 **다중 에이전트 시스템** 같은 덜 알려진 AI 접근법. +* "고전적인" 지식 표현 및 추론([GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence))을 포함한 다양한 인공지능 접근 방식. +* 현대 AI의 핵심인 **신경망**과 **딥러닝**. 이 중요한 개념들을 두 가지 인기 프레임워크인 [TensorFlow](http://Tensorflow.org)와 [PyTorch](http://pytorch.org)로 코드 예시를 통해 설명합니다. +* 이미지 및 텍스트 작업을 위한 **신경 아키텍처**. 최신 모델을 다루지만 최신 연구 동향은 일부 부족할 수 있습니다. +* 덜 알려진 AI 접근 방식인 **유전 알고리즘**과 **멀티 에이전트 시스템**. -이 커리큘럼에서 다루지 않는 것: +이 커리큘럼에서 다루지 않는 내용: -> [Microsoft Learn 컬렉션에서 이 과정 관련 모든 추가 자료를 찾아보세요](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) +> [이 코스에 대한 추가 자료는 Microsoft Learn 컬렉션에서 모두 확인하세요](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) -* **비즈니스에서의 AI** 활용 사례. Microsoft Learn의 [비즈니스 사용자용 AI 입문](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 학습 경로나 [INSEAD](https://www.insead.edu/)와 협력해 개발된 [AI 비즈니스 스쿨](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)을 추천합니다. -* 고전적인 기계 학습으로, 이는 우리의 [초보자를 위한 기계 학습 커리큘럼](http://github.com/Microsoft/ML-for-Beginners)에 잘 설명되어 있습니다. -* **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**를 활용한 실용 AI 애플리케이션. 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 서비스와 생성형 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 모듈부터 시작할 것을 추천합니다. -* [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) 같은 특정 ML 클라우드 프레임워크. [Azure Machine Learning으로 기계 학습 솔루션 개발 및 운영](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum)과 [Azure Databricks로 기계 학습 솔루션 개발 및 운영](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 학습 경로를 권장합니다. -* **대화형 AI**와 **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, 더 자세한 내용은 [이 블로그 게시물](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)을 참조하세요. -* 딥러닝의 **심층 수학**. 이를 위해 Ian Goodfellow, Yoshua Bengio, Aaron Courville의 [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618) 교재(온라인: [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/))를 추천합니다. +* **비즈니스에서의 AI** 활용 사례. Microsoft Learn의 [비즈니스 사용자를 위한 AI 입문](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 학습 경로나 [INSEAD](https://www.insead.edu/)와 협력하여 개발한 [AI 비즈니스 스쿨](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)를 추천합니다. +* 잘 설명된 **고전 머신러닝**은 [초보자를 위한 머신러닝 커리큘럼](http://github.com/Microsoft/ML-for-Beginners)에서 확인하세요. +* **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**를 활용한 실용적인 AI 응용. 이를 위해 Microsoft Learn 모듈에서 [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 서비스와 생성 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 등을 시작해 보세요. +* [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) 등 특정 머신러닝 클라우드 프레임워크. [Azure Machine Learning으로 머신러닝 솔루션 구축 및 운영](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum)과 [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 추천합니다. +* **대화형 AI**와 **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 글](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)도 참고하세요. +* 딥러닝의 **심도 있는 수학적 이론**. 이 주제는 Ian Goodfellow, Yoshua Bengio, Aaron Courville의 [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)을 추천하며, 온라인으로도 [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)에서 볼 수 있습니다. -_클라우드 AI_ 주제를 부드럽게 소개하려면 [Azure에서 인공지능 시작하기](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 학습 경로를 참고하세요. +_클라우드에서의 AI_에 대한 부드러운 입문을 원한다면 [Azure에서 인공지능 시작하기](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) 학습 경로를 고려해 보세요. -# 콘텐츠 +# 목차 -| | 강의 링크 | PyTorch/Keras/TensorFlow | 실험실 | -| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | -| 0 | [코스 설정](./lessons/0-course-setup/setup.md) | [개발 환경 설정](./lessons/0-course-setup/how-to-run.md) | | +| | 수업 링크 | PyTorch/Keras/TensorFlow | 실습 | +| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------- | +| 0 | [코스 세팅](./lessons/0-course-setup/setup.md) | [개발 환경 설정하기](./lessons/0-course-setup/how-to-run.md) | | | I | [**AI 소개**](./lessons/1-Intro/README.md) | | | -| 01 | [AI 개요 및 역사](./lessons/1-Intro/README.md) | - | - | -| II | **상징적 AI** | +| 01 | [AI 소개 및 역사](./lessons/1-Intro/README.md) | - | - | +| II | **상징적 인공지능** | | 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) | [랩](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) | -| 04 | [다층 퍼셉트론과 자체 프레임워크 만들기](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [노트북](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [랩](./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) | [랩](./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 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) | [랩](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) | -| 07 | [합성곱 신경망](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN 구조](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [랩](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) | -| 08 | [사전학습 네트워크 및 전이 학습](./lessons/4-ComputerVision/08-TransferLearning/README.md) 및 [학습 팁](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [랩](./lessons/4-ComputerVision/08-TransferLearning/lab/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 퍼셉트론과 자체 프레임워크 만들기](./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 탐색하기](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 네트워크와 전이 학습](./lessons/4-ComputerVision/08-TransferLearning/README.md) 및 [학습 요령](./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) | | 09 | [오토인코더 및 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 | [생성적 적대 신경망 및 예술적 스타일 전송](./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) | [랩](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) | +| 10 | [생성적 적대 신경망 및 예술 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 탐색](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)| -| 13 | [텍스트 표현. Bag of Words / 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) | | +| 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 탐색하기](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. 자체 임베딩 훈련](./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) | [랩](./lessons/5-NLP/15-LanguageModeling/lab/README.md) | +| 15 | [언어 모델링. 나만의 임베딩 학습하기](./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 | [생성 순환 신경망](./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) | [랩](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) | +| 17 | [생성 순환 신경망](./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) | [랩](./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) | | +| 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 소수 샷 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 기법** || | | 21 | [유전 알고리즘](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [노트북](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | | -| 22 | [딥 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) | [랩](./lessons/6-Other/22-DeepRL/lab/README.md) | -| 23 | [멀티 에이전트 시스템](./lessons/6-Other/23-MultiagentSystems/README.md) | | | +| 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 | **추가 자료** | | | | 25 | [멀티모달 네트워크, CLIP 및 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [노트북](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | | -## 각 강의는 다음을 포함합니다 - +## 각 강의에는 * 사전 학습 자료 -* 실행 가능한 주피터 노트북. 보통 프레임워크(**PyTorch** 또는 **TensorFlow**)별로 제공됩니다. 실행 가능한 노트북에는 이론 자료도 많아 주제를 이해하려면 노트북 버전 중 하나(Pytorch 또는 TensorFlow)를 반드시 학습해야 합니다. -* 일부 주제에 대해 **랩**이 제공되어, 학습한 내용을 특정 문제에 적용해 볼 수 있는 기회를 제공합니다. -* 관련 주제를 다루는 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 모듈 링크를 포함한 섹션도 있습니다. +* 프레임워크(**PyTorch** 또는 **TensorFlow**)에 특화된 실행 가능한 Jupyter 노트북. 실행 가능한 노트북에는 많은 이론적 내용도 포함되어 있어 주제를 이해하려면 적어도 한 버전의 노트북(PyTorch 또는 TensorFlow 중 하나)을 꼭 살펴봐야 합니다. +* 일부 주제에 대해 제공되는 **랩**으로, 학습한 내용을 특정 문제에 적용해 볼 수 있는 기회를 제공합니다. +* 관련 주제를 다루는 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 모듈로 연결되는 링크가 포함된 섹션도 있습니다. ## 시작하기 ### 🎯 AI가 처음인가요? 여기서 시작하세요! -AI가 완전 처음이고 빠르게 직접 해볼 수 있는 예제를 찾는다면, [**초보자 친화 예제**](./examples/README.md)를 확인하세요! 여기에는 다음이 포함됩니다: +AI가 완전히 처음이고 빠르고 실습 위주의 예제를 원한다면, [**초보자 친화적 예제**](./examples/README.md)를 확인해 보세요! 여기에는 다음이 포함됩니다: -- 🌟 **Hello AI World** - 당신의 첫 AI 프로그램 (패턴 인식) -- 🧠 **간단한 신경망** - 처음부터 신경망 구축하기 +- 🌟 **Hello AI World** - 당신의 첫 AI 프로그램(패턴 인식) +- 🧠 **간단한 신경망** - 신경망을 처음부터 만들어 보기 +- 🖼️ **이미지 분류기** - 자세한 주석과 함께 이미지 분류 +- 💬 **텍스트 감성 분석** - 긍정/부정 텍스트 분석 -- 🖼️ **이미지 분류기** - 상세 주석과 함께 이미지 분류 -- 💬 **텍스트 감정 분석** - 긍정/부정 텍스트 분석 - -이 예제들은 전체 커리큘럼을 시작하기 전에 AI 개념을 이해하는 데 도움이 되도록 설계되었습니다. +이 예제들은 전체 커리큘럼에 들어가기 전에 AI 개념을 이해하는 데 도움이 되도록 설계되었습니다. ### 📚 전체 커리큘럼 설정 -- 개발 환경 설정을 도와드리는 [설정 수업](./lessons/0-course-setup/setup.md)을 만들었습니다. - 교육자를 위해서도 [커리큘럼 설정 수업](./lessons/0-course-setup/for-teachers.md)을 만들었습니다! +- 개발 환경 설정을 돕기 위해 [설정 강의](./lessons/0-course-setup/setup.md)를 만들었습니다. +- 교육자를 위해서는 [커리큘럼 설정 강의](./lessons/0-course-setup/for-teachers.md)도 준비되어 있습니다! - VSCode 또는 Codespace에서 [코드를 실행하는 방법](./lessons/0-course-setup/how-to-run.md) -다음 단계를 따르세요: +다음 단계를 따라 주세요: -저장소 포크하기: 이 페이지 오른쪽 상단의 "Fork" 버튼을 클릭하세요. +저장소 포크하기: 이 페이지 우측 상단의 "Fork" 버튼을 클릭하세요. 저장소 클론하기: `git clone https://github.com/microsoft/AI-For-Beginners.git` -이 저장소를 별표(🌟) 표시하여 나중에 쉽게 찾으세요. +나중에 더 쉽게 찾으려면 이 저장소에 별(🌟)을 꼭 눌러주세요. -## 다른 학습자 만나기 +## 학습자 모임 -본 [공식 AI Discord 서버](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)에 참여하여 이 강좌를 수강하는 다른 학습자들과 교류하고 도움을 받으세요. +이 과정을 수강하는 다른 학습자들과 만나고 네트워킹하며 지원을 받을 수 있는 [공식 AI Discord 서버](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)에 참여하세요. -제품 피드백이나 질문이 있으면 [Azure AI Foundry 개발자 포럼](https://aka.ms/foundry/forum)을 방문하세요. +제품 피드백이나 질문이 있으면 [Azure AI Foundry 개발자 포럼](https://aka.ms/foundry/forum)을 방문해 주세요. ## 퀴즈 -> **퀴즈에 대한 안내**: 모든 퀴즈는 Quiz-app 폴더인 etc\quiz-app에 포함되어 있으며, 또는 [온라인에서 여기](https://ff-quizzes.netlify.app/)에서 확인할 수 있습니다. 퀴즈는 수업 내에서 링크되어 있고, 퀴즈 앱은 로컬에서 실행하거나 Azure에 배포할 수 있습니다. `quiz-app` 폴더 내 지침을 따르세요. 점차적으로 현지화되고 있습니다. +> **퀴즈에 관한 주의 사항**: 모든 퀴즈는 etc\quiz-app 폴더 내 Quiz-app 폴더에 들어 있으며, [온라인](https://ff-quizzes.netlify.app/)에서도 이용 가능합니다. 각 강의 내에서 연결되어 있고, 퀴즈 앱은 로컬에서 실행하거나 Azure에 배포할 수 있습니다. `quiz-app` 폴더 내 지침을 따르세요. 점차적으로 현지화 작업이 진행 중입니다. -## 도움 요청 +## 도움이 필요합니다 -제안 사항이 있거나 철자 또는 코드 오류를 발견했나요? 문제를 제기하거나 풀 리퀘스트를 만들어주세요. +제안 사항이 있거나 철자 또는 코드 오류를 발견했다면 이슈를 제기하거나 풀 리퀘스트를 만들어 주세요. ## 특별 감사 -* **✍️ 주요 저자:** [Dmitry Soshnikov](http://soshnikov.com), PhD -* **🔥 편집자:** [Jen Looper](https://twitter.com/jenlooper), PhD -* **🎨 스케치노트 일러스트레이터:** [Tomomi Imura](https://twitter.com/girlie_mac) -* **✅ 퀴즈 제작자:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/) -* **🙏 핵심 기여자:** [Evgenii Pishchik](https://github.com/Pe4enIks) +* **✍️ 주요 저자:** [Dmitry Soshnikov](http://soshnikov.com), PhD +* **🔥 편집자:** [Jen Looper](https://twitter.com/jenlooper), PhD +* **🎨 스케치노트 일러스트레이터:** [Tomomi Imura](https://twitter.com/girlie_mac) +* **✅ 퀴즈 제작자:** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/) +* **🙏 핵심 공헌자:** [Evgenii Pishchik](https://github.com/Pe4enIks) -## 기타 커리큘럼 +## 다른 커리큘럼 -우리 팀은 다른 커리큘럼도 제작합니다! 확인해보세요: +우리 팀에서 다른 커리큘럼도 제작합니다! 확인해 보세요: ### LangChain @@ -201,7 +209,7 @@ AI가 완전 처음이고 빠르게 직접 해볼 수 있는 예제를 찾는다 --- -### Copilot 시리즈 +### 코파일럿 시리즈 [![Copilot for AI Paired Programming](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) [![Copilot for C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) [![Copilot Adventure](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) @@ -209,11 +217,11 @@ AI가 완전 처음이고 빠르게 직접 해볼 수 있는 예제를 찾는다 ## 도움 받기 -AI 앱 개발 중에 막히거나 질문이 있으면 MCP에 대해 토론하는 다른 학습자 및 경험 많은 개발자들과 교류하세요. 질문이 환영받고 지식이 자유롭게 공유되는 지원 커뮤니티입니다. +AI 앱 개발 중에 막히거나 질문이 있으면 MCP에 대해 학습하는 동료 학습자와 경험 많은 개발자들이 모여 있는 토론에 참여하세요. 질문이 언제든 환영받고 지식을 자유롭게 공유하는 따뜻한 커뮤니티입니다. [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -개발 중 제품 피드백이나 오류가 있으면 다음을 방문하세요: +제품 피드백이나 오류가 있으면 다음을 방문하세요: [![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) @@ -221,5 +229,5 @@ AI 앱 개발 중에 막히거나 질문이 있으면 MCP에 대해 토론하는 **면책 조항**: -이 문서는 AI 번역 서비스 [Co-op Translator](https://github.com/Azure/co-op-translator)를 사용하여 번역되었습니다. 정확성을 위해 노력하고 있으나, 자동 번역은 오류나 부정확성이 포함될 수 있음을 유의해 주시기 바랍니다. 원본 문서의 원어 텍스트가 권위 있는 자료로 간주되어야 합니다. 중요한 정보에 대해서는 전문 인력의 번역을 권장합니다. 본 번역 사용으로 인해 발생하는 오해나 잘못된 해석에 대해 당사는 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 있음을 양지해 주시기 바랍니다. 원문 문서가 권위 있는 출처로 간주되어야 합니다. 중요한 정보에 대해서는 전문가의 인간 번역을 권장합니다. 본 번역 사용으로 인해 발생하는 오해나 잘못된 해석에 대해 당사는 책임을 지지 않습니다. \ No newline at end of file diff --git a/translations/ko/lessons/2-Symbolic/MSConceptGraph.ipynb b/translations/ko/lessons/2-Symbolic/MSConceptGraph.ipynb index 72ed0d74..cc8d10d8 100644 --- a/translations/ko/lessons/2-Symbolic/MSConceptGraph.ipynb +++ b/translations/ko/lessons/2-Symbolic/MSConceptGraph.ipynb @@ -1,539 +1,532 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": { - "collapsed": true - }, - "source": [ - "## Microsoft Concept Graph - 이 API는 더 이상 사용 불가능하지만 개념을 이해하려면 노트북을 확인하세요\n", - "\n", - "[Microsoft Concept Graph](https://concept.research.microsoft.com/)는 인터넷에서 추출된 용어의 대규모 분류 체계로, 개념 간의 `is-a` 관계를 포함하고 있습니다.\n", - "\n", - "Context Graph는 두 가지 형태로 제공됩니다:\n", - " * 다운로드 가능한 대규모 텍스트 파일\n", - " * REST API\n", - "\n", - "통계:\n", - " * 5401933개의 고유 개념\n", - " * 12551613개의 고유 인스턴스\n", - " * 87603947개의 `is-a` 관계\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## 웹 서비스 사용하기\n", - "\n", - "웹 서비스는 특정 개념이 다양한 그룹에 속할 확률을 추정하기 위한 여러 호출을 제공합니다. 자세한 정보는 [여기](https://concept.research.microsoft.com/Home/Api)에서 확인할 수 있습니다. \n", - "다음은 호출을 위한 샘플 URL입니다: `https://api.conceptnet.io/query?start=/c/en/microsoft&rel=/r/IsA&limit=10`\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": { - "trusted": true - }, - "outputs": [], - "source": [ - "import urllib\n", - "import json\n", - "\n", - "def http(x):\n", - " response = urllib.request.urlopen(x)\n", - " data = response.read()\n", - " return data.decode('utf-8')\n", - "\n", - "def query(x):\n", - " concept = x.lower().replace(' ', '_')\n", - " url = \"https://api.conceptnet.io/query?start=/c/en/{}&rel=/r/IsA&limit=10\".format(\n", - " urllib.parse.quote(concept))\n", - " try:\n", - " result = json.loads(http(url))\n", - " except Exception:\n", - " return {}\n", - " edges = result.get('edges', [])\n", - " if not edges:\n", - " return {}\n", - " total_weight = sum(edge['weight'] for edge in edges)\n", - " if total_weight == 0:\n", - " return {}\n", - " return {edge['end']['label']: edge['weight'] / total_weight for edge in edges}\n", - "\n", - "query('microsoft')" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "뉴스 제목을 상위 개념으로 분류해 봅시다. 뉴스 제목을 얻기 위해 [NewsApi.org](http://newsapi.org) 서비스를 사용할 것입니다. 서비스를 사용하려면 자체 API 키를 얻어야 합니다. 웹사이트에 방문하여 무료 개발자 플랜에 등록하세요.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": { - "trusted": true - }, - "outputs": [], - "source": [ - "newsapi_key = ''\n", - "def get_news(country='us'):\n", - " res = json.loads(http(\"https://newsapi.org/v2/top-headlines?country={0}&apiKey={1}\".format(country,newsapi_key)))\n", - " return res['articles']\n", - "\n", - "all_titles = [x['title'] for x in get_news('us')+get_news('gb')]" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['Covid-19 Live Updates: Vaccines and Boosters News - The New York Times',\n", - " 'Ukrainians Flee Mariupol as Russian Forces Push to Take Port City - The Wall Street Journal',\n", - " 'Bond Yields Jump, Stock Futures Rise After Powell Says Fed Is Ready to Be More Aggressive - The Wall Street Journal',\n", - " 'Putin critic Alexei Navalny found guilty by Russian court - New York Post ',\n", - " \"Supreme Court nominee Ketanji Brown Jackson will face questions at confirmation hearing's second day - CNN\",\n", - " '2 teachers killed at Swedish high school, student arrested - ABC News',\n", - " 'Clues to Covid-19’s Next Moves Come From Sewers - The Wall Street Journal',\n", - " 'Republicans to roll dice by grilling Jackson over child-pornography sentencing decisions | TheHill - The Hill',\n", - " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", - " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", - " \"US stocks whipsawed overnight after Fed Chair Powell's remarks - Fox Business\",\n", - " \"'We've learned absolutely nothing': Tests could again be in short supply if Covid surges - POLITICO\",\n", - " \"Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\",\n", - " 'China searches for victims, flight recorders after first plane crash in 12 years - Reuters',\n", - " 'Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters',\n", - " 'Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español',\n", - " 'Powers Remain and Threats Lurk as Women’s Sweet 16 Is Set - The New York Times',\n", - " 'Webb Space Telescope Begins Multi-Instrument Alignment - SciTechDaily',\n", - " \"UConn vs UCF - NCAA women's tournament second-round highlights - March Madness\",\n", - " 'Bucking Republican Trend, Indiana Governor Vetoes Transgender Sports Bill - The New York Times',\n", - " \"Maggie Fox dead: Coronation Street and Shameless actress dies after 'sudden accident' - Mirror Online - The Mirror\",\n", - " 'China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent',\n", - " 'Daniel Morgan murder: damning report condemns Met police - The Guardian',\n", - " 'What to expect from Rishi Sunak’s Spring Statement - BBC.com',\n", - " 'UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian',\n", - " \"Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\",\n", - " 'Brass Eye’s outtakes show the brutal TV comedy was the tip of an iceberg - The Guardian',\n", - " \"Vladimir Putin threatens civilians to break Mariupol's spirit - The Times\",\n", - " 'Shell U-turn on Cambo oilfield would threaten green targets, say campaigners - The Guardian',\n", - " 'St Helens dog attack: Girl aged 17 months killed at home - BBC',\n", - " \"PlayStation to buy 'Assassin's Creed' veteran Jade Raymond's Haven Studios - NME\",\n", - " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", - " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", - " 'Nintendo Switch finally has folders • Eurogamer.net - Eurogamer.net',\n", - " 'FA to “find a solution” as Liverpool fan group blasts “shambolic” Wembley travel - This Is Anfield',\n", - " 'Manchester United transfer news LIVE Erik ten Hag latest and Man Utd manager updates - Manchester Evening News',\n", - " 'Inflation raises cost of UK government borrowing in February; crude oil up again – business live - The Guardian',\n", - " 'Alexei Navalny: Kremlin critic found guilty of large-scale fraud and contempt of court by Russian court - Sky News',\n", - " \"UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\",\n", - " 'Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian']" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "all_titles" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "우선, 우리는 뉴스 제목에서 명사를 추출할 수 있기를 원합니다. 이를 위해 `TextBlob` 라이브러리를 사용할 것이며, 이는 이러한 일반적인 NLP 작업을 크게 간소화합니다.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: textblob in c:\\winapp\\miniconda3\\lib\\site-packages (0.17.1)\n", - "Requirement already satisfied: nltk>=3.1 in c:\\winapp\\miniconda3\\lib\\site-packages (from textblob) (3.5)\n", - "Requirement already satisfied: joblib in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (1.0.1)\n", - "Requirement already satisfied: regex in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (2021.11.10)\n", - "Requirement already satisfied: tqdm in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (4.61.2)\n", - "Requirement already satisfied: click in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (8.0.3)\n", - "Requirement already satisfied: colorama in c:\\winapp\\miniconda3\\lib\\site-packages (from click->nltk>=3.1->textblob) (0.4.4)\n", - "Finished.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[nltk_data] Downloading package brown to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package brown is already up-to-date!\n", - "[nltk_data] Downloading package punkt to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package punkt is already up-to-date!\n", - "[nltk_data] Downloading package wordnet to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package wordnet is already up-to-date!\n", - "[nltk_data] Downloading package averaged_perceptron_tagger to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package averaged_perceptron_tagger is already up-to-\n", - "[nltk_data] date!\n", - "[nltk_data] Downloading package conll2000 to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package conll2000 is already up-to-date!\n", - "[nltk_data] Downloading package movie_reviews to\n", - "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", - "[nltk_data] Package movie_reviews is already up-to-date!\n" - ] - } - ], - "source": [ - "import sys\n", - "!{sys.executable} -m pip install textblob\n", - "!{sys.executable} -m textblob.download_corpora\n", - "from textblob import TextBlob" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "{'covid-19 live updates': 1,\n", - " 'vaccines': 1,\n", - " 'boosters': 1,\n", - " 'york': 4,\n", - " 'ukrainians flee mariupol': 1,\n", - " 'forces push': 1,\n", - " 'port city': 1,\n", - " 'wall street journal': 3,\n", - " 'bond yields': 1,\n", - " 'futures rise': 1,\n", - " 'powell says fed': 1,\n", - " 'ready': 1,\n", - " 'be': 1,\n", - " 'aggressive': 1,\n", - " 'putin': 3,\n", - " 'alexei navalny': 2,\n", - " 'russian': 2,\n", - " 'supreme court nominee': 1,\n", - " 'ketanji brown jackson': 1,\n", - " \"confirmation hearing 's\": 1,\n", - " 'cnn': 1,\n", - " 'swedish': 1,\n", - " 'high school': 1,\n", - " 'abc': 1,\n", - " 'clues': 1,\n", - " 'covid-19': 1,\n", - " '’ s': 2,\n", - " 'moves': 1,\n", - " 'sewers': 1,\n", - " 'roll dice': 1,\n", - " 'jackson': 1,\n", - " 'decisions |': 1,\n", - " 'thehill': 1,\n", - " 'clear': 2,\n", - " 'chemical weapons': 2,\n", - " 'ukraine': 3,\n", - " 'claims president': 2,\n", - " 'biden': 2,\n", - " 'nasa': 2,\n", - " 'solar system': 2,\n", - " 'daily mail': 3,\n", - " 'us stocks': 1,\n", - " 'fed chair powell': 1,\n", - " \"'s remarks\": 1,\n", - " 'fox': 1,\n", - " \"'we 've\": 1,\n", - " 'tests': 1,\n", - " 'covid': 1,\n", - " 'politico': 1,\n", - " 'duchess': 1,\n", - " 'cambridge': 1,\n", - " 'swaps khaki jungle gear': 1,\n", - " 'vampire': 1,\n", - " 'wife': 1,\n", - " 'belize': 1,\n", - " 'china': 2,\n", - " 'flight recorders': 1,\n", - " 'plane crash': 1,\n", - " 'reuters': 2,\n", - " 'russian oligarch': 1,\n", - " 'abramovich': 1,\n", - " 'live': 1,\n", - " 'russia': 2,\n", - " 'stops talks': 1,\n", - " 'japan': 1,\n", - " 'español': 1,\n", - " 'powers remain': 1,\n", - " 'threats lurk': 1,\n", - " 'set': 1,\n", - " 'webb': 1,\n", - " 'telescope begins multi-instrument alignment': 1,\n", - " 'scitechdaily': 1,\n", - " 'uconn': 1,\n", - " 'ucf': 1,\n", - " 'ncaa': 1,\n", - " \"women 's tournament second-round highlights\": 1,\n", - " 'march madness': 1,\n", - " 'bucking republican trend': 1,\n", - " 'indiana': 1,\n", - " 'vetoes transgender': 1,\n", - " 'bill': 1,\n", - " 'maggie fox': 1,\n", - " 'coronation': 1,\n", - " 'shameless': 1,\n", - " \"'sudden accident\": 1,\n", - " 'mirror online': 1,\n", - " 'mirror': 2,\n", - " 'plane crash –': 1,\n", - " 'search': 1,\n", - " 'moment flight': 1,\n", - " 'daniel morgan': 1,\n", - " 'report condemns': 1,\n", - " 'met': 1,\n", - " 'guardian': 6,\n", - " 'rishi sunak': 1,\n", - " '’ s spring': 1,\n", - " 'statement': 1,\n", - " 'bbc.com': 1,\n", - " 'uk': 3,\n", - " 'ireland': 1,\n", - " 'euro': 1,\n", - " 'vladimir putin': 2,\n", - " \"'s 'lover\": 1,\n", - " 'brass eye': 1,\n", - " '’ s outtakes': 1,\n", - " 'brutal tv comedy': 1,\n", - " 'threatens civilians': 1,\n", - " 'mariupol': 1,\n", - " \"'s spirit\": 1,\n", - " 'shell u-turn': 1,\n", - " 'cambo': 1,\n", - " 'green targets': 1,\n", - " 'st helens': 1,\n", - " 'dog attack': 1,\n", - " 'girl': 1,\n", - " 'bbc': 1,\n", - " 'playstation': 1,\n", - " \"'assassin 's\": 1,\n", - " 'creed': 1,\n", - " 'jade raymond': 1,\n", - " 'haven studios': 1,\n", - " 'nme': 1,\n", - " 'nintendo switch': 1,\n", - " 'folders •': 1,\n", - " 'eurogamer.net': 2,\n", - " 'fa': 1,\n", - " 'solution ”': 1,\n", - " 'liverpool': 1,\n", - " 'fan group blasts “ shambolic ”': 1,\n", - " 'wembley': 1,\n", - " 'anfield': 1,\n", - " 'manchester': 1,\n", - " 'live erik': 1,\n", - " 'hag': 1,\n", - " 'utd': 1,\n", - " 'manager updates': 1,\n", - " 'manchester evening': 1,\n", - " 'inflation': 1,\n", - " 'government borrowing': 1,\n", - " 'february': 1,\n", - " 'crude oil': 1,\n", - " '– business': 1,\n", - " 'kremlin': 1,\n", - " 'large-scale fraud': 1,\n", - " 'sky': 1,\n", - " 'natural gas': 1,\n", - " 'gazprom': 1,\n", - " 'retail unit': 1,\n", - " 'insider': 1,\n", - " 'zaghari-ratcliffe': 1,\n", - " 'hunt': 1,\n", - " 'iran': 1,\n", - " 'debt payment': 1}" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "w = {}\n", - "for x in all_titles:\n", - " for n in TextBlob(x).noun_phrases:\n", - " if n in w:\n", - " w[n].append(x)\n", - " else:\n", - " w[n]=[x]\n", - "{ x:len(w[x]) for x in w.keys()}" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "우리는 명사가 큰 주제 그룹을 제공하지 않는다는 것을 알 수 있습니다. 개념 그래프에서 얻은 더 일반적인 용어로 명사를 대체해 봅시다. 이것은 약간의 시간이 걸릴 것입니다. 왜냐하면 각 명사 구에 대해 REST 호출을 수행하고 있기 때문입니다.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": { - "trusted": true - }, - "outputs": [], - "source": [ - "w = {}\n", - "for x in all_titles:\n", - " for noun in TextBlob(x).noun_phrases:\n", - " terms = query(noun)\n", - " for term in [u for u in terms.keys() if terms[u]>0.1]:\n", - " if term in w:\n", - " w[term].append(x)\n", - " else:\n", - " w[term]=[x]" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "{'city': 9,\n", - " 'brand': 4,\n", - " 'place': 9,\n", - " 'town': 4,\n", - " 'factor': 4,\n", - " 'film': 4,\n", - " 'nation': 11,\n", - " 'state': 5,\n", - " 'person': 4,\n", - " 'organization': 5,\n", - " 'publication': 10,\n", - " 'market': 5,\n", - " 'economy': 4,\n", - " 'company': 6,\n", - " 'newspaper': 6,\n", - " 'relationship': 6}" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "{ x:len(w[x]) for x in w.keys() if len(w[x])>3}" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "metadata": { - "trusted": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "ECONOMY:\n", - "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", - "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", - "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", - "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", - "\n", - "NATION:\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", - "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", - "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", - "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", - "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", - "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", - "UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian\n", - "Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", - "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", - "Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian\n", - "\n", - "PERSON:\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", - "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", - "Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters\n", - "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n" - ] - } - ], - "source": [ - "print('\\nECONOMY:\\n'+'\\n'.join(w['economy']))\n", - "print('\\nNATION:\\n'+'\\n'.join(w['nation']))\n", - "print('\\nPERSON:\\n'+'\\n'.join(w['person']))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "\n---\n\n**면책 조항**: \n이 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 문서의 원어 버전이 권위 있는 출처로 간주되어야 합니다. 중요한 정보의 경우, 전문적인 인간 번역을 권장합니다. 이 번역 사용으로 인해 발생하는 오해나 잘못된 해석에 대해 당사는 책임을 지지 않습니다.\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3.7.4 64-bit (conda)", - "metadata": { - "interpreter": { - "hash": "86193a1ab0ba47eac1c69c1756090baa3b420b3eea7d4aafab8b85f8b312f0c5" - } - }, - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.5" - }, - "coopTranslator": { - "original_hash": "7b3f1fc049371bcf8649ac9fefdf0413", - "translation_date": "2025-10-03T18:52:23+00:00", - "source_file": "lessons/2-Symbolic/MSConceptGraph.ipynb", - "language_code": "ko" - } + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "## ConceptNet을 사용한 개념 그래프\n", + "\n", + "> **참고:** 원래의 [Microsoft Concept Graph](https://concept.research.microsoft.com/) API는 더 이상 사용할 수 없습니다. 이 노트북은 유사한 개념 간 `is-a` 관계를 가진 무료 공개 지식 그래프인 [ConceptNet](https://conceptnet.io/)을 대체로 사용하도록 업데이트되었습니다.\n", + "\n", + "[ConceptNet](https://conceptnet.io/)은 `IsA`, `PartOf`, `UsedFor` 등과 같은 관계를 가진 개념들의 대규모 의미 네트워크입니다. 다음과 같이 제공됩니다:\n", + " * 다운로드 가능한 데이터 파일\n", + " * REST API (API 키 필요 없음)\n", + "\n", + "ConceptNet 통계:\n", + " * 800만 개 이상의 노드\n", + " * 8300만 개 이상의 엣지, 83개 언어에 걸쳐 있음\n" + ] }, - "nbformat": 4, - "nbformat_minor": 2 + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## ConceptNet 웹 서비스 사용하기\n", + "\n", + "[ConceptNet](https://conceptnet.io/)는 개념 간의 `is-a` (IsA) 관계를 탐색할 수 있는 REST API를 제공합니다. API 키가 필요하지 않습니다. \n", + "다음은 호출할 샘플 URL입니다: `https://api.conceptnet.io/query?start=/c/en/microsoft&rel=/r/IsA&limit=10`\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "import urllib\n", + "import json\n", + "\n", + "def http(x):\n", + " response = urllib.request.urlopen(x)\n", + " data = response.read()\n", + " return data.decode('utf-8')\n", + "\n", + "def query(x):\n", + " concept = x.lower().replace(' ', '_')\n", + " url = \"https://api.conceptnet.io/query?start=/c/en/{}&rel=/r/IsA&limit=10\".format(\n", + " urllib.parse.quote(concept))\n", + " try:\n", + " result = json.loads(http(url))\n", + " except Exception:\n", + " return {}\n", + " edges = result.get('edges', [])\n", + " if not edges:\n", + " return {}\n", + " total_weight = sum(edge['weight'] for edge in edges)\n", + " if total_weight == 0:\n", + " return {}\n", + " return {edge['end']['label']: edge['weight'] / total_weight for edge in edges}\n", + "\n", + "query('microsoft')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "뉴스 제목을 상위 개념을 사용하여 분류해 봅시다. 뉴스 제목을 얻기 위해 [NewsApi.org](http://newsapi.org) 서비스를 사용할 것입니다. 서비스를 사용하려면 자신의 API 키를 받아야 합니다. 웹사이트에 접속하여 무료 개발자 플랜에 등록하세요.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "newsapi_key = ''\n", + "def get_news(country='us'):\n", + " res = json.loads(http(\"https://newsapi.org/v2/top-headlines?country={0}&apiKey={1}\".format(country,newsapi_key)))\n", + " return res['articles']\n", + "\n", + "all_titles = [x['title'] for x in get_news('us')+get_news('gb')]" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['Covid-19 Live Updates: Vaccines and Boosters News - The New York Times',\n", + " 'Ukrainians Flee Mariupol as Russian Forces Push to Take Port City - The Wall Street Journal',\n", + " 'Bond Yields Jump, Stock Futures Rise After Powell Says Fed Is Ready to Be More Aggressive - The Wall Street Journal',\n", + " 'Putin critic Alexei Navalny found guilty by Russian court - New York Post ',\n", + " \"Supreme Court nominee Ketanji Brown Jackson will face questions at confirmation hearing's second day - CNN\",\n", + " '2 teachers killed at Swedish high school, student arrested - ABC News',\n", + " 'Clues to Covid-19’s Next Moves Come From Sewers - The Wall Street Journal',\n", + " 'Republicans to roll dice by grilling Jackson over child-pornography sentencing decisions | TheHill - The Hill',\n", + " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", + " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", + " \"US stocks whipsawed overnight after Fed Chair Powell's remarks - Fox Business\",\n", + " \"'We've learned absolutely nothing': Tests could again be in short supply if Covid surges - POLITICO\",\n", + " \"Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\",\n", + " 'China searches for victims, flight recorders after first plane crash in 12 years - Reuters',\n", + " 'Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters',\n", + " 'Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español',\n", + " 'Powers Remain and Threats Lurk as Women’s Sweet 16 Is Set - The New York Times',\n", + " 'Webb Space Telescope Begins Multi-Instrument Alignment - SciTechDaily',\n", + " \"UConn vs UCF - NCAA women's tournament second-round highlights - March Madness\",\n", + " 'Bucking Republican Trend, Indiana Governor Vetoes Transgender Sports Bill - The New York Times',\n", + " \"Maggie Fox dead: Coronation Street and Shameless actress dies after 'sudden accident' - Mirror Online - The Mirror\",\n", + " 'China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent',\n", + " 'Daniel Morgan murder: damning report condemns Met police - The Guardian',\n", + " 'What to expect from Rishi Sunak’s Spring Statement - BBC.com',\n", + " 'UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian',\n", + " \"Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\",\n", + " 'Brass Eye’s outtakes show the brutal TV comedy was the tip of an iceberg - The Guardian',\n", + " \"Vladimir Putin threatens civilians to break Mariupol's spirit - The Times\",\n", + " 'Shell U-turn on Cambo oilfield would threaten green targets, say campaigners - The Guardian',\n", + " 'St Helens dog attack: Girl aged 17 months killed at home - BBC',\n", + " \"PlayStation to buy 'Assassin's Creed' veteran Jade Raymond's Haven Studios - NME\",\n", + " '‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent',\n", + " 'NASA confirms there are 5,000 planets outside our solar system - Daily Mail',\n", + " 'Nintendo Switch finally has folders • Eurogamer.net - Eurogamer.net',\n", + " 'FA to “find a solution” as Liverpool fan group blasts “shambolic” Wembley travel - This Is Anfield',\n", + " 'Manchester United transfer news LIVE Erik ten Hag latest and Man Utd manager updates - Manchester Evening News',\n", + " 'Inflation raises cost of UK government borrowing in February; crude oil up again – business live - The Guardian',\n", + " 'Alexei Navalny: Kremlin critic found guilty of large-scale fraud and contempt of court by Russian court - Sky News',\n", + " \"UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\",\n", + " 'Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian']" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "all_titles" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "무엇보다도, 우리는 뉴스 제목에서 명사를 추출할 수 있기를 원합니다. 이를 위해 `TextBlob` 라이브러리를 사용할 것이며, 이 라이브러리는 이러한 전형적인 자연어 처리 작업을 많이 단순화해줍니다.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Requirement already satisfied: textblob in c:\\winapp\\miniconda3\\lib\\site-packages (0.17.1)\n", + "Requirement already satisfied: nltk>=3.1 in c:\\winapp\\miniconda3\\lib\\site-packages (from textblob) (3.5)\n", + "Requirement already satisfied: joblib in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (1.0.1)\n", + "Requirement already satisfied: regex in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (2021.11.10)\n", + "Requirement already satisfied: tqdm in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (4.61.2)\n", + "Requirement already satisfied: click in c:\\winapp\\miniconda3\\lib\\site-packages (from nltk>=3.1->textblob) (8.0.3)\n", + "Requirement already satisfied: colorama in c:\\winapp\\miniconda3\\lib\\site-packages (from click->nltk>=3.1->textblob) (0.4.4)\n", + "Finished.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[nltk_data] Downloading package brown to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package brown is already up-to-date!\n", + "[nltk_data] Downloading package punkt to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package punkt is already up-to-date!\n", + "[nltk_data] Downloading package wordnet to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package wordnet is already up-to-date!\n", + "[nltk_data] Downloading package averaged_perceptron_tagger to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package averaged_perceptron_tagger is already up-to-\n", + "[nltk_data] date!\n", + "[nltk_data] Downloading package conll2000 to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package conll2000 is already up-to-date!\n", + "[nltk_data] Downloading package movie_reviews to\n", + "[nltk_data] C:\\Users\\dmitryso\\AppData\\Roaming\\nltk_data...\n", + "[nltk_data] Package movie_reviews is already up-to-date!\n" + ] + } + ], + "source": [ + "import sys\n", + "!{sys.executable} -m pip install textblob\n", + "!{sys.executable} -m textblob.download_corpora\n", + "from textblob import TextBlob" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'covid-19 live updates': 1,\n", + " 'vaccines': 1,\n", + " 'boosters': 1,\n", + " 'york': 4,\n", + " 'ukrainians flee mariupol': 1,\n", + " 'forces push': 1,\n", + " 'port city': 1,\n", + " 'wall street journal': 3,\n", + " 'bond yields': 1,\n", + " 'futures rise': 1,\n", + " 'powell says fed': 1,\n", + " 'ready': 1,\n", + " 'be': 1,\n", + " 'aggressive': 1,\n", + " 'putin': 3,\n", + " 'alexei navalny': 2,\n", + " 'russian': 2,\n", + " 'supreme court nominee': 1,\n", + " 'ketanji brown jackson': 1,\n", + " \"confirmation hearing 's\": 1,\n", + " 'cnn': 1,\n", + " 'swedish': 1,\n", + " 'high school': 1,\n", + " 'abc': 1,\n", + " 'clues': 1,\n", + " 'covid-19': 1,\n", + " '’ s': 2,\n", + " 'moves': 1,\n", + " 'sewers': 1,\n", + " 'roll dice': 1,\n", + " 'jackson': 1,\n", + " 'decisions |': 1,\n", + " 'thehill': 1,\n", + " 'clear': 2,\n", + " 'chemical weapons': 2,\n", + " 'ukraine': 3,\n", + " 'claims president': 2,\n", + " 'biden': 2,\n", + " 'nasa': 2,\n", + " 'solar system': 2,\n", + " 'daily mail': 3,\n", + " 'us stocks': 1,\n", + " 'fed chair powell': 1,\n", + " \"'s remarks\": 1,\n", + " 'fox': 1,\n", + " \"'we 've\": 1,\n", + " 'tests': 1,\n", + " 'covid': 1,\n", + " 'politico': 1,\n", + " 'duchess': 1,\n", + " 'cambridge': 1,\n", + " 'swaps khaki jungle gear': 1,\n", + " 'vampire': 1,\n", + " 'wife': 1,\n", + " 'belize': 1,\n", + " 'china': 2,\n", + " 'flight recorders': 1,\n", + " 'plane crash': 1,\n", + " 'reuters': 2,\n", + " 'russian oligarch': 1,\n", + " 'abramovich': 1,\n", + " 'live': 1,\n", + " 'russia': 2,\n", + " 'stops talks': 1,\n", + " 'japan': 1,\n", + " 'español': 1,\n", + " 'powers remain': 1,\n", + " 'threats lurk': 1,\n", + " 'set': 1,\n", + " 'webb': 1,\n", + " 'telescope begins multi-instrument alignment': 1,\n", + " 'scitechdaily': 1,\n", + " 'uconn': 1,\n", + " 'ucf': 1,\n", + " 'ncaa': 1,\n", + " \"women 's tournament second-round highlights\": 1,\n", + " 'march madness': 1,\n", + " 'bucking republican trend': 1,\n", + " 'indiana': 1,\n", + " 'vetoes transgender': 1,\n", + " 'bill': 1,\n", + " 'maggie fox': 1,\n", + " 'coronation': 1,\n", + " 'shameless': 1,\n", + " \"'sudden accident\": 1,\n", + " 'mirror online': 1,\n", + " 'mirror': 2,\n", + " 'plane crash –': 1,\n", + " 'search': 1,\n", + " 'moment flight': 1,\n", + " 'daniel morgan': 1,\n", + " 'report condemns': 1,\n", + " 'met': 1,\n", + " 'guardian': 6,\n", + " 'rishi sunak': 1,\n", + " '’ s spring': 1,\n", + " 'statement': 1,\n", + " 'bbc.com': 1,\n", + " 'uk': 3,\n", + " 'ireland': 1,\n", + " 'euro': 1,\n", + " 'vladimir putin': 2,\n", + " \"'s 'lover\": 1,\n", + " 'brass eye': 1,\n", + " '’ s outtakes': 1,\n", + " 'brutal tv comedy': 1,\n", + " 'threatens civilians': 1,\n", + " 'mariupol': 1,\n", + " \"'s spirit\": 1,\n", + " 'shell u-turn': 1,\n", + " 'cambo': 1,\n", + " 'green targets': 1,\n", + " 'st helens': 1,\n", + " 'dog attack': 1,\n", + " 'girl': 1,\n", + " 'bbc': 1,\n", + " 'playstation': 1,\n", + " \"'assassin 's\": 1,\n", + " 'creed': 1,\n", + " 'jade raymond': 1,\n", + " 'haven studios': 1,\n", + " 'nme': 1,\n", + " 'nintendo switch': 1,\n", + " 'folders •': 1,\n", + " 'eurogamer.net': 2,\n", + " 'fa': 1,\n", + " 'solution ”': 1,\n", + " 'liverpool': 1,\n", + " 'fan group blasts “ shambolic ”': 1,\n", + " 'wembley': 1,\n", + " 'anfield': 1,\n", + " 'manchester': 1,\n", + " 'live erik': 1,\n", + " 'hag': 1,\n", + " 'utd': 1,\n", + " 'manager updates': 1,\n", + " 'manchester evening': 1,\n", + " 'inflation': 1,\n", + " 'government borrowing': 1,\n", + " 'february': 1,\n", + " 'crude oil': 1,\n", + " '– business': 1,\n", + " 'kremlin': 1,\n", + " 'large-scale fraud': 1,\n", + " 'sky': 1,\n", + " 'natural gas': 1,\n", + " 'gazprom': 1,\n", + " 'retail unit': 1,\n", + " 'insider': 1,\n", + " 'zaghari-ratcliffe': 1,\n", + " 'hunt': 1,\n", + " 'iran': 1,\n", + " 'debt payment': 1}" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "w = {}\n", + "for x in all_titles:\n", + " for n in TextBlob(x).noun_phrases:\n", + " if n in w:\n", + " w[n].append(x)\n", + " else:\n", + " w[n]=[x]\n", + "{ x:len(w[x]) for x in w.keys()}" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "명사가 우리에게 큰 주제 그룹을 제공하지 않는다는 것을 알 수 있습니다. 명사를 개념 그래프에서 얻은 더 일반적인 용어로 대체해 보겠습니다. 각 명사구마다 REST 호출을 수행하기 때문에 시간이 좀 걸릴 것입니다.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "trusted": true + }, + "outputs": [], + "source": [ + "w = {}\n", + "for x in all_titles:\n", + " for noun in TextBlob(x).noun_phrases:\n", + " terms = query(noun)\n", + " for term in [u for u in terms.keys() if terms[u]>0.1]:\n", + " if term in w:\n", + " w[term].append(x)\n", + " else:\n", + " w[term]=[x]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'city': 9,\n", + " 'brand': 4,\n", + " 'place': 9,\n", + " 'town': 4,\n", + " 'factor': 4,\n", + " 'film': 4,\n", + " 'nation': 11,\n", + " 'state': 5,\n", + " 'person': 4,\n", + " 'organization': 5,\n", + " 'publication': 10,\n", + " 'market': 5,\n", + " 'economy': 4,\n", + " 'company': 6,\n", + " 'newspaper': 6,\n", + " 'relationship': 6}" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "{ x:len(w[x]) for x in w.keys() if len(w[x])>3}" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "trusted": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "ECONOMY:\n", + "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", + "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", + "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", + "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", + "\n", + "NATION:\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", + "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", + "China searches for victims, flight recorders after first plane crash in 12 years - Reuters\n", + "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", + "Live updates: Russia stops talks with Japan over sanctions - The Associated Press - en Español\n", + "China plane crash – live: Search for survivors continues as witness describes moment flight fell from sky - The Independent\n", + "UK and Republic of Ireland in line to host Euro 2028 after no one else bids - The Guardian\n", + "Friends beg Vladimir Putin's 'lover' to persuade him to end Ukraine invasion - The Mirror\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", + "UK prepares to nationalize Russia natural gas giant Gazprom's retail unit - Business Insider\n", + "Zaghari-Ratcliffe: Hunt calls for inquiry into delay over Iran debt payment - The Guardian\n", + "\n", + "PERSON:\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n", + "Duchess of Cambridge swaps khaki jungle gear for Vampire's Wife dress on Belize trip - Daily Mail\n", + "Second superyacht linked to Russian oligarch Abramovich docks in Turkey - Reuters\n", + "‘Clear sign’ Putin considering using chemical weapons in Ukraine, claims President Biden - The Independent\n" + ] + } + ], + "source": [ + "print('\\nECONOMY:\\n'+'\\n'.join(w['economy']))\n", + "print('\\nNATION:\\n'+'\\n'.join(w['nation']))\n", + "print('\\nPERSON:\\n'+'\\n'.join(w['person']))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "---\n\n\n**면책 조항**: \n이 문서는 AI 번역 서비스 [Co-op Translator](https://github.com/Azure/co-op-translator)를 사용하여 번역되었습니다. 정확성을 위해 노력하고 있으나, 자동 번역에는 오류나 부정확성이 포함될 수 있음을 유의하시기 바랍니다. 원문은 해당 언어의 원본 문서를 권위 있는 출처로 간주해야 합니다. 중요한 정보의 경우 전문 원어민 번역을 권장합니다. 본 번역 사용으로 인한 오해나 잘못된 해석에 대해서는 당사가 책임지지 않습니다.\n\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.7.4 64-bit (conda)", + "metadata": { + "interpreter": { + "hash": "86193a1ab0ba47eac1c69c1756090baa3b420b3eea7d4aafab8b85f8b312f0c5" + } + }, + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.5" + } + }, + "nbformat": 4, + "nbformat_minor": 2 } \ No newline at end of file