microsoft/AI-For-Beginners

[](https://github.com/microsoft/AI-For-Beginners/blob/main/LICENSE) [](https://GitHub.com/microsoft/AI-For-Beginners/graphs/contributors/) [](https://GitHub.com/microsoft/AI-For-Beginners/issues/) [](https://GitHub.com/microsoft/AI-For-Beginners/pulls/) [](http://makeapullrequest.com) [](https://GitHub.com/microsoft/AI-For-Beginners/watchers/) [](https://GitHub.com/microsoft/AI-For-Beginners/network/) [](https://GitHub.com/microsoft/AI-For-Beginners/stargazers/) [](https://mybinder.org/v2/gh/microsoft/ai-for-beginners/HEAD) [](https://gitter.im/Microsoft/ai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge) [](https://discord.gg/nTYy5BXMWG) # 人工智能入门 - 课程 || |:---:| | AI For Beginners - _Sketchnote by [@girlie_mac](https://twitter.com/girlie_mac)_ | 通过我们为期 12 周、共 24 节课的课程，探索**人工智能** (AI) 的世界！它包含实用的课程、测验和实验。该课程对初学者很友好，涵盖了 TensorFlow 和 PyTorch 等工具，以及 AI 伦理。 ### 🌐 多语言支持 #### 通过 GitHub Action 支持（自动化且始终最新） [Arabic](./translations/ar/README.md) | [Bengali](./translations/bn/README.md) | [Bulgarian](./translations/bg/README.md) | [Burmese (Myanmar)](./translations/my/README.md) | [Chinese (Simplified)](./translations/zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](./translations/zh-HK/README.md) | [Chinese (Traditional, Macau)](./translations/zh-MO/README.md) | [Chinese (Traditional, Taiwan)](./translations/zh-TW/README.md) | [Croatian](./translations/hr/README.md) | [Czech](./translations/cs/README.md) | [Danish](./translations/da/README.md) | [Dutch](./translations/nl/README.md) | [Estonian](./translations/et/README.md) | [Finnish](./translations/fi/README.md) | [French](./translations/fr/README.md) | [German](./translations/de/README.md) | [Greek](./translations/el/README.md) | [Hebrew](./translations/he/README.md) | [Hindi](./translations/hi/README.md) | [Hungarian](./translations/hu/README.md) | [Indonesian](./translations/id/README.md) | [Italian](./translations/it/README.md) | [Japanese](./translations/ja/README.md) | [Kannada](./translations/kn/README.md) | [Khmer](./translations/km/README.md) | [Korean](./translations/ko/README.md) | [Lithuanian](./translations/lt/README.md) | [Malay](./translations/ms/README.md) | [Malayalam](./translations/ml/README.md) | [Marathi](./translations/mr/README.md) | [Nepali](./translations/ne/README.md) | [Nigerian Pidgin](./translations/pcm/README.md) | [Norwegian](./translations/no/README.md) | [Persian (Farsi)](./translations/fa/README.md) | [Polish](./translations/pl/README.md) | [Portuguese (Brazil)](./translations/pt-BR/README.md) | [Portuguese (Portugal)](./translations/pt-PT/README.md) | [Punjabi (Gurmukhi)](./translations/pa/README.md) | [Romanian](./translations/ro/README.md) | [Russian](./translations/ru/README.md) | [Serbian (Cyrillic)](./translations/sr/README.md) | [Slovak](./translations/sk/README.md) | [Slovenian](./translations/sl/README.md) | [Spanish](./translations/es/README.md) | [Swahili](./translations/sw/README.md) | [Swedish](./translations/sv/README.md) | [Tagalog (Filipino)](./translations/tl/README.md) | [Tamil](./translations/ta/README.md) | [Telugu](./translations/te/README.md) | [Thai](./translations/th/README.md) | [Turkish](./translations/tr/README.md) | [Ukrainian](./translations/uk/README.md) | [Urdu](./translations/ur/README.md) | [Vietnamese](./translations/vi/README.md) **如果您希望支持其他翻译语言，请查看[此处](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)列出的语言** ## 您将学到什么 **[课程思维导图](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)** 在本课程中，您将学到： * 人工智能的不同方法，包括“经典”的符号方法，涉及**知识表示**和推理（[GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)）。 * **神经网络**和**深度学习**，这是现代 AI 的核心。我们将使用两个最流行的框架——[TensorFlow](http://Tensorflow.org) 和 [PyTorch](http://pytorch.org) 中的代码来阐述这些重要主题背后的概念。 * 用于处理图像和文本的**神经网络架构**。我们将涵盖最新的模型，但在最前沿的技术方面可能略有欠缺。 * 不那么主流的 AI 方法，例如**遗传算法**和**多智能体系统**。 本课程不会涵盖以下内容： * **AI 在商业领域**的商业案例。建议考虑学习 Microsoft Learn 上的[面向商业用户的 AI 简介](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum)学习路径，或者与 [INSEAD](https://www.insead.edu/) 合作开发的 [AI 商学院](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum)。 * **经典机器学习**，这部分内容在我们的[面向初学者的机器学习课程](http://github.com/Microsoft/ML-for-Beginners)中有详细说明。 * 使用 **[认知服务](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)** 构建的实际 AI 应用。为此，我们建议您从 Microsoft Learn 中关于[视觉](https://docs.microsoft.com/learn/paths/create-computer-vision-solutions-azure-cognitive-services/?WT.mc_id=academic-77998-bethanycheum)、[自然语言处理](https://docs.microsoft.com/learn/paths/explore-natural-language-processing/?WT.mc_id=academic-77998-bethanycheum)、**[使用 Azure OpenAI 服务的生成式 AI](https://learn.microsoft.com/en-us/training/paths/develop-ai-solutions-azure-openai/?WT.mc_id=academic-77998-bethanycheum)** 等模块开始。 * 特定的机器学习**云框架**，例如 [Azure 机器学习](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum)、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum) 或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum)。建议考虑学习[使用 Azure 机器学习构建和操作机器学习解决方案](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum)以及[使用 Azure Databricks 构建和操作机器学习解决方案](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum)学习路径。 * **对话式 AI** 和**聊天机器人**。这里有一个单独的[创建对话式 AI 解决方案](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum)学习路径，您也可以参考[这篇博客文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/)了解更多详情。 * 深度学习背后的**深层数学原理**。为此，我们推荐 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 编写的《Deep Learning》，该书也可在线获取，网址为 [https://www.deeplearningbook.org/](https://www.deeplearningbook.org/)。 如需对 _云端 AI_ 主题进行简单介绍，您可以考虑学习 [Azure 上的人工智能入门](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum)学习路径。 # 内容 | | 课程链接 | PyTorch/Keras/TensorFlow | 实验 | | :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ | | 0 | [课程设置](./lessons/0-course-setup/setup.md) | [设置您的开发环境](./lessons/0-course-setup/how-to-run.md) | | | I | [**AI 简介**](./lessons/1-Intro/README.md) | | | | 01 | [AI 简介与历史](./lessons/1-Intro/README.md) | - | - | | II | **符号 AI** | | 02 | [知识表示与专家系统](./lessons/2-Symbolic/README.md) | [专家系统](./lessons/2-Symbolic/Animals.ipynb) / [本体](./lessons/2-Symbolic/FamilyOntology.ipynb) /[概念图](./lessons/2-Symbolic/MSConceptGraph.ipynb) | | | III | [**神经网络简介**](./lessons/3-NeuralNetworks/README.md) ||| | 03 | [感知机](./lessons/3-NeuralNetworks/03-Perceptron/README.md) | [Notebook](./lessons/3-NeuralNetworks/03-Perceptron/Perceptron.ipynb) | [实验](./lessons/3-NeuralNetworks/03-Perceptron/lab/README.md) | | 04 | [多层感知机与创建我们自己的框架](./lessons/3-NeuralNetworks/04-OwnFramework/README.md) | [Notebook](./lessons/3-NeuralNetworks/04-OwnFramework/OwnFramework.ipynb) | [实验](./lessons/3-NeuralNetworks/04-OwnFramework/lab/README.md) | | 05 | [框架简介 (PyTorch/TensorFlow) 与过拟合](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [实验](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) | | IV | [**计算机视觉**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [探索 Microsoft Azure 上的计算机视觉](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) | | 06 | [计算机视觉简介。OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [实验](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) | | 07 | [卷积神经网络](./lessons/4-ComputerVision/07-ConvNets/README.md) & [CNN 架构](./lessons/4-ComputerVision/07-ConvNets/CNN_Architectures.md) | [PyTorch](./lessons/4-ComputerVision/07-ConvNets/ConvNetsPyTorch.ipynb) /[TensorFlow](./lessons/4-ComputerVision/07-ConvNets/ConvNetsTF.ipynb) | [实验](./lessons/4-ComputerVision/07-ConvNets/lab/README.md) | | 08 | [预训练网络与迁移学习](./lessons/4-ComputerVision/08-TransferLearning/README.md) 和 [训练技巧](./lessons/4-ComputerVision/08-TransferLearning/TrainingTricks.md) | [PyTorch](./lessons/4-ComputerVision/08-TransferLearning/TransferLearningPyTorch.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [实验](./lessons/4-ComputerVision/08-TransferLearning/lab/README.md) | | 09 | [自编码器与 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 | [生成对抗网络与艺术风格迁移](./lessons/4-ComputerVision/10-GANs/README.md) | [PyTorch](./lessons/4-ComputerVision/10-GANs/GANPyTorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/10-GANs/GANTF.ipynb) | | | 11 | [目标检测](./lessons/4-ComputerVision/11-ObjectDetection/README.md) | [TensorFlow](./lessons/4-ComputerVision/11-ObjectDetection/ObjectDetection.ipynb) | [实验](./lessons/4-ComputerVision/11-ObjectDetection/lab/README.md) | | 12 | [语义分割。U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | | | V | [**自然语言处理**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [探索 Microsoft Azure 上的自然语言处理](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)| | 13 | [文本表示。Bow/TF-IDF](./lessons/5-NLP/13-TextRep/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/13-TextRep/TextRepresentationTF.ipynb) | | | 14 | [语义词嵌入。Word2Vec 和 GloVe](./lessons/5-NLP/14-Embeddings/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/14-Embeddings/EmbeddingsTF.ipynb) | | | 15 | [语言建模。训练您自己的词嵌入](./lessons/5-NLP/15-LanguageModeling/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-PyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/15-LanguageModeling/CBoW-TF.ipynb) | [实验](./lessons/5-NLP/15-LanguageModeling/lab/README.md) | | 16 | [循环神经网络](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | | | 17 | [生成式循环网络](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [实验]() | | 18 | [Transformer。BERT。](./lessons/5-NLP/18-Transformers/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersPyTorch.ipynb) /[TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/18-Transformers/TransformersTF.ipynb) | | | 19 | [命名实体识别](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [实验](./lessons/5-NLP/19-NER/lab/README.md) | | 20 | [大语言模型、提示编程与少样本任务](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | | | VI | **其他 AI 技术** || | | 21 | [遗传算法](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | | | 22 | [深度强化学习](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [实验](./lessons/6-Other/22-DeepRL/lab/README.md) | | 23 | [多智能体系统](./lessons/6-Other/23-MultiagentSystems/README.md) | | | | VII | **AI 伦理** | | | | 24 | [AI 伦理与负责任的 AI](./lessons/7-Ethics/README.md) | [Microsoft Learn：负责任的 AI 原则](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | | | IX | **附加内容** | | | | 25 | [多模态网络、CLIP 与 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | | ## 每节课包含 * 预读材料 * 可执行的 Jupyter Notebook，通常是针对特定框架的（**PyTorch** 或 **TensorFlow**）。可执行 notebook 中还包含大量理论材料，因此要理解该主题，您至少需要通读一个版本的 notebook（PyTorch 或 TensorFlow）。 * 部分主题提供**实验**，让您有机会尝试将所学知识应用到特定问题上。 * 部分章节包含指向涵盖相关主题的 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 模块的链接。 ## 入门指南 ### 🎯 AI 新手？从这里开始！ 如果您完全是 AI 新手，并且想要快速、上手的示例，请查看我们的[**面向初学者的示例**](./examples/README.md)！这包括： - 🌟 **Hello AI World** - 您的第一个 AI 程序（模式识别） - 🧠 **简单的神经网络** - 从零开始构建神经网络 - 🖼️ **图像分类器** - 带有详细注释的图像分类 - 💬 **文本情感分析** - 分析正面/负面文本 这些示例旨在帮助您在学习完整课程之前先了解 AI 概念。 ### 📚 完整课程设置 - 我们创建了一个[设置课程](./lessons/0-course-setup/setup.md)来帮助您设置开发环境。- 对于教育工作者，我们也为您创建了[课程设置课程](./lessons/0-course-setup/for-teachers.md)！ - 如何[在 VSCode 或 Codespace 中运行代码](./lessons/0-course-setup/how-to-run.md) 请按照以下步骤操作： Fork 仓库：点击此页面右上角的“Fork”按钮。 克隆仓库：`git clone https://github.com/microsoft/AI-For-Beginners.git` ## 测验 ## 其他课程 我们的团队还制作了其他课程！请查看： ### LangChain ## [](https://aka.ms/langchain4j-for-beginners) [](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) [](https://github.com/microsoft/langchain-for-beginners?WT.mc_id=m365-94501-dwahlin) ### Azure / Edge / MCP / Agents [](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst) ### 生成式 AI 系列 [](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) [-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) [-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) [-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst) ### 核心学习 [](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) [](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) [](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) [](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) [](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) ### Copilot 系列 [](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) [](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) ## 获取帮助 如果您在构建 AI 应用时遇到困难或有任何疑问，请加入其他学习者和经验丰富的开发人员的行列，一起讨论 MCP。这是一个充满支持的社区，欢迎大家提问并自由分享知识。 [](https://discord.gg/nTYy5BXMWG) 如果您在构建过程中有产品反馈或遇到错误，请访问： [](https://aka.ms/foundry/forum)

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