microsoft--ai-for-beginners
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<!-- WEHUB_ZH_README -->
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> [!NOTE]
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> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。
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> [English](./README.en.md) · [原始项目](https://github.com/microsoft/AI-For-Beginners) · [上游 README](https://github.com/microsoft/AI-For-Beginners/blob/HEAD/README.md)
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> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。
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[](https://github.com/microsoft/AI-For-Beginners/blob/main/LICENSE)
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[](https://GitHub.com/microsoft/AI-For-Beginners/graphs/contributors/)
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[](https://GitHub.com/microsoft/AI-For-Beginners/issues/)
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[](https://GitHub.com/microsoft/AI-For-Beginners/pulls/)
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[](http://makeapullrequest.com)
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[](https://GitHub.com/microsoft/AI-For-Beginners/watchers/)
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[](https://GitHub.com/microsoft/AI-For-Beginners/network/)
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[](https://GitHub.com/microsoft/AI-For-Beginners/stargazers/)
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[](https://mybinder.org/v2/gh/microsoft/ai-for-beginners/HEAD)
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[](https://gitter.im/Microsoft/ai-for-beginners?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
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[](https://discord.gg/nTYy5BXMWG)
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# 人工智能入门 - 课程体系
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|:---:|
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| 人工智能入门 - _手绘笔记作者 [@girlie_mac](https://twitter.com/girlie_mac)_ |
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通过我们为期 12 周、共 24 课时的课程体系，探索 **人工智能**（Artificial Intelligence，AI）的世界！课程包含实践课时、测验和实验。本课程对初学者友好，涵盖 TensorFlow 和 PyTorch 等工具，以及 AI 伦理相关内容。
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### 🌐 多语言支持
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#### 通过 GitHub Action 支持（自动化且始终保持最新）
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<!-- CO-OP TRANSLATOR LANGUAGES TABLE START -->
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[阿拉伯语](./translations/ar/README.md) | [孟加拉语](./translations/bn/README.md) | [保加利亚语](./translations/bg/README.md) | [缅甸语](./translations/my/README.md) | [简体中文](./translations/zh-CN/README.md) | [繁体中文（香港）](./translations/zh-HK/README.md) | [繁体中文（澳门）](./translations/zh-MO/README.md) | [繁体中文（台湾）](./translations/zh-TW/README.md) | [克罗地亚语](./translations/hr/README.md) | [捷克语](./translations/cs/README.md) | [丹麦语](./translations/da/README.md) | [荷兰语](./translations/nl/README.md) | [爱沙尼亚语](./translations/et/README.md) | [芬兰语](./translations/fi/README.md) | [法语](./translations/fr/README.md) | [德语](./translations/de/README.md) | [希腊语](./translations/el/README.md) | [希伯来语](./translations/he/README.md) | [印地语](./translations/hi/README.md) | [匈牙利语](./translations/hu/README.md) | [印尼语](./translations/id/README.md) | [意大利语](./translations/it/README.md) | [日语](./translations/ja/README.md) | [卡纳达语](./translations/kn/README.md) | [高棉语](./translations/km/README.md) | [韩语](./translations/ko/README.md) | [立陶宛语](./translations/lt/README.md) | [马来语](./translations/ms/README.md) | [马拉雅拉姆语](./translations/ml/README.md) | [马拉地语](./translations/mr/README.md) | [尼泊尔语](./translations/ne/README.md) | [尼日利亚皮钦语](./translations/pcm/README.md) | [挪威语](./translations/no/README.md) | [波斯语（法尔西语）](./translations/fa/README.md) | [波兰语](./translations/pl/README.md) | [葡萄牙语（巴西）](./translations/pt-BR/README.md) | [葡萄牙语（葡萄牙）](./translations/pt-PT/README.md) | [旁遮普语（古木基文）](./translations/pa/README.md) | [罗马尼亚语](./translations/ro/README.md) | [俄语](./translations/ru/README.md) | [塞尔维亚语（西里尔文）](./translations/sr/README.md) | [斯洛伐克语](./translations/sk/README.md) | [斯洛文尼亚语](./translations/sl/README.md) | [西班牙语](./translations/es/README.md) | [斯瓦希里语](./translations/sw/README.md) | [瑞典语](./translations/sv/README.md) | [他加禄语（菲律宾语）](./translations/tl/README.md) | [泰米尔语](./translations/ta/README.md) | [泰卢固语](./translations/te/README.md) | [泰语](./translations/th/README.md) | [土耳其语](./translations/tr/README.md) | [乌克兰语](./translations/uk/README.md) | [乌尔都语](./translations/ur/README.md) | [越南语](./translations/vi/README.md)
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> **更倾向于在本地克隆？**
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>
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> 本仓库包含 50 多种语言翻译，会显著增加下载体积。若要在克隆时排除翻译内容，请使用 sparse checkout：
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>
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> **Bash / macOS / Linux：**
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> ```bash
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> git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git
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> cd AI-For-Beginners
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> git sparse-checkout set --no-cone '/*' '!translations' '!translated_images'
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> ```
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>
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> **CMD (Windows)：**
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> ```cmd
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> git clone --filter=blob:none --sparse https://github.com/microsoft/AI-For-Beginners.git
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> cd AI-For-Beginners
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> git sparse-checkout set --no-cone "/*" "!translations" "!translated_images"
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> ```
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>
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> 这样即可获得完成课程所需的全部内容，且下载速度会快得多。
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<!-- CO-OP TRANSLATOR LANGUAGES TABLE END -->
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**如果您希望添加更多翻译语言，支持的语言列表请见[此处](https://github.com/Azure/co-op-translator/blob/main/getting_started/supported-languages.md)**
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## 加入社区
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[](https://discord.gg/nTYy5BXMWG)
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## 你将学到什么
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**[课程思维导图](http://soshnikov.com/courses/ai-for-beginners/mindmap.html)**
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在本课程中，你将学习：
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* 人工智能的不同方法，包括采用 **知识表示**（Knowledge Representation）与推理的“经典”符号主义方法（[GOFAI](https://en.wikipedia.org/wiki/Symbolic_artificial_intelligence)).
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* **神经网络**（Neural Networks）与**深度学习**（Deep Learning），它们是现代 AI 的核心。我们将使用两种最流行的框架中的代码来阐释这些重要主题背后的概念——[TensorFlow](http://Tensorflow.org) 和 [PyTorch](http://pytorch.org).
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* 用于处理图像和文本的**神经网络架构**（Neural Architectures）。我们将介绍较新的模型，但在最前沿（state-of-the-art）方面可能略有不足。
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* 较冷门的 AI 方法，例如**遗传算法**（Genetic Algorithms）和**多智能体系统**（Multi-Agent Systems）。
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本课程不涵盖的内容：
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> [在我们的 Microsoft Learn 合集中查找本课程的所有附加资源](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)
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* 在商业中使用 **AI** 的业务案例。建议学习 Microsoft Learn 上的 [面向商业用户的人工智能入门](https://docs.microsoft.com/learn/paths/introduction-ai-for-business-users/?WT.mc_id=academic-77998-bethanycheum) 学习路径，或与 [INSEAD](https://www.insead.edu/). 合作开发的 [AI Business School](https://www.microsoft.com/ai/ai-business-school/?WT.mc_id=academic-77998-bethanycheum),
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* **经典机器学习**（Classic Machine Learning），相关内容在我们的 [机器学习入门课程体系](http://github.com/Microsoft/ML-for-Beginners). 中有详尽介绍。
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* 使用 **[Cognitive Services](https://azure.microsoft.com/services/cognitive-services/?WT.mc_id=academic-77998-bethanycheum)**. 构建的实用 AI 应用。对此，我们建议你从 Microsoft Learn 的以下模块入手：[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)** 等。
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* 特定的 ML **云框架**（Cloud Frameworks），例如 [Azure Machine Learning](https://azure.microsoft.com/services/machine-learning/?WT.mc_id=academic-77998-bethanycheum),、[Microsoft Fabric](https://learn.microsoft.com/en-us/training/paths/get-started-fabric/?WT.mc_id=academic-77998-bethanycheum), 或 [Azure Databricks](https://docs.microsoft.com/learn/paths/data-engineer-azure-databricks?WT.mc_id=academic-77998-bethanycheum).。可考虑使用 [Build and operate machine learning solutions with Azure Machine Learning](https://docs.microsoft.com/learn/paths/build-ai-solutions-with-azure-ml-service/?WT.mc_id=academic-77998-bethanycheum) 和 [Build and Operate Machine Learning Solutions with Azure Databricks](https://docs.microsoft.com/learn/paths/build-operate-machine-learning-solutions-azure-databricks/?WT.mc_id=academic-77998-bethanycheum) 学习路径。
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* **对话式 AI**（Conversational AI）与**聊天机器人**（Chat Bots）。另有单独的 [Create conversational AI solutions](https://docs.microsoft.com/learn/paths/create-conversational-ai-solutions/?WT.mc_id=academic-77998-bethanycheum) 学习路径，你也可以参考[这篇博客文章](https://soshnikov.com/azure/hello-bot-conversational-ai-on-microsoft-platform/) 了解更多细节。
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* 深度学习背后的**高深数学**（Deep Mathematics）。对此，我们推荐 Ian Goodfellow、Yoshua Bengio 和 Aaron Courville 合著的 [Deep Learning](https://www.amazon.com/Deep-Learning-Adaptive-Computation-Machine/dp/0262035618)，也可在线阅读：[https://www.deeplearningbook.org/](https://www.deeplearningbook.org/).
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若想温和地了解 _AI in the Cloud_（云端人工智能）相关主题，你可以考虑学习 [在 Azure 上开启人工智能之旅](https://docs.microsoft.com/learn/paths/get-started-with-artificial-intelligence-on-azure/?WT.mc_id=academic-77998-bethanycheum) Learning Path。
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# 内容
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| | Lesson Link | PyTorch/Keras/TensorFlow | Lab |
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| :-: | :------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: | ------------------------------------------------------------------------------ |
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| 0 | [课程设置](./lessons/0-course-setup/setup.md) | [配置开发环境](./lessons/0-course-setup/how-to-run.md) | |
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| I | [**人工智能简介**](./lessons/1-Intro/README.md) | | |
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| 01 | [人工智能简介与历史](./lessons/1-Intro/README.md) | - | - |
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| II | **符号人工智能（Symbolic AI）** |
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| 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（Ontology）](./lessons/2-Symbolic/FamilyOntology.ipynb) /[概念图（Concept Graph）](./lessons/2-Symbolic/MSConceptGraph.ipynb) | |
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| III | [**神经网络入门**](./lessons/3-NeuralNetworks/README.md) |||
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| 03 | [感知器（Perceptron）](./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) |
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| 04 | [多层感知器与构建自有框架](./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) |
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| 05 | [框架入门（PyTorch/TensorFlow）与过拟合（Overfitting）](./lessons/3-NeuralNetworks/05-Frameworks/README.md) | [PyTorch](./lessons/3-NeuralNetworks/05-Frameworks/IntroPyTorch.ipynb) / [Keras](./lessons/3-NeuralNetworks/05-Frameworks/IntroKeras.ipynb) / [TensorFlow](./lessons/3-NeuralNetworks/05-Frameworks/IntroKerasTF.ipynb) | [实验](./lessons/3-NeuralNetworks/05-Frameworks/lab/README.md) |
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| IV | [**计算机视觉（Computer Vision）**](./lessons/4-ComputerVision/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-computer-vision-pytorch/?WT.mc_id=academic-77998-cacaste) / [TensorFlow](https://docs.microsoft.com/learn/modules/intro-computer-vision-TensorFlow/?WT.mc_id=academic-77998-cacaste)| [在 Microsoft Azure 上探索计算机视觉](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) |
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| 06 | [计算机视觉入门。OpenCV](./lessons/4-ComputerVision/06-IntroCV/README.md) | [Notebook](./lessons/4-ComputerVision/06-IntroCV/OpenCV.ipynb) | [实验](./lessons/4-ComputerVision/06-IntroCV/lab/README.md) |
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| 07 | [卷积神经网络（Convolutional Neural Networks）](./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) |
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| 08 | [预训练网络与迁移学习（Transfer Learning）](./lessons/4-ComputerVision/08-TransferLearning/README.md) and [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) |
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| 09 | [自编码器（Autoencoders）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) | |
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| 10 | [生成对抗网络（GAN）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) | |
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| 11 | [目标检测（Object Detection）](./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) |
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| 12 | [语义分割（Semantic Segmentation）。U-Net](./lessons/4-ComputerVision/12-Segmentation/README.md) | [PyTorch](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationPytorch.ipynb) / [TensorFlow](./lessons/4-ComputerVision/12-Segmentation/SemanticSegmentationTF.ipynb) | |
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| V | [**自然语言处理（Natural Language Processing）**](./lessons/5-NLP/README.md) | [PyTorch](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-pytorch/?WT.mc_id=academic-77998-cacaste) /[TensorFlow](https://docs.microsoft.com/learn/modules/intro-natural-language-processing-TensorFlow/?WT.mc_id=academic-77998-cacaste) | [在 Microsoft Azure 上探索自然语言处理](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum)|
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| 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) | |
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| 14 | [语义词嵌入（Word Embeddings）。Word2Vec 与 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) | |
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| 15 | [语言建模（Language Modeling）。训练自有嵌入](./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) |
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| 16 | [循环神经网络（Recurrent Neural Networks）](./lessons/5-NLP/16-RNN/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNPyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/16-RNN/RNNTF.ipynb) | |
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| 17 | [生成式循环网络](./lessons/5-NLP/17-GenerativeNetworks/README.md) | [PyTorch](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativePyTorch.ipynb) / [TensorFlow](https://github.com/microsoft/AI-For-Beginners/blob/main/lessons/5-NLP/17-GenerativeNetworks/GenerativeTF.ipynb) | [实验](./lessons/5-NLP/17-GenerativeNetworks/lab/README.md) |
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| 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) | |
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| 19 | [命名实体识别（Named Entity Recognition）](./lessons/5-NLP/19-NER/README.md) | [TensorFlow](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/19-NER/NER-TF.ipynb) | [实验](./lessons/5-NLP/19-NER/lab/README.md) |
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| 20 | [大语言模型（Large Language Models）、提示编程（Prompt Programming）与少样本任务（Few-Shot Tasks）](./lessons/5-NLP/20-LangModels/README.md) | [PyTorch](https://microsoft.github.io/AI-For-Beginners/lessons/5-NLP/20-LangModels/GPT-PyTorch.ipynb) | |
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| VI | **其他 AI 技术** || |
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| 21 | [遗传算法（Genetic Algorithms）](./lessons/6-Other/21-GeneticAlgorithms/README.md) | [Notebook](./lessons/6-Other/21-GeneticAlgorithms/Genetic.ipynb) | |
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| 22 | [深度强化学习（Deep Reinforcement Learning）](./lessons/6-Other/22-DeepRL/README.md) | [PyTorch](./lessons/6-Other/22-DeepRL/CartPole-RL-PyTorch.ipynb) /[TensorFlow](./lessons/6-Other/22-DeepRL/CartPole-RL-TF.ipynb) | [实验](./lessons/6-Other/22-DeepRL/lab/README.md) |
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| 23 | [多智能体系统（Multi-Agent Systems）](./lessons/6-Other/23-MultiagentSystems/README.md) | | |
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| VII | **AI 伦理** | | |
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| 24 | [AI 伦理与负责任 AI（Responsible AI）](./lessons/7-Ethics/README.md) | [Microsoft Learn：负责任 AI 原则](https://docs.microsoft.com/learn/paths/responsible-ai-business-principles/?WT.mc_id=academic-77998-cacaste) | |
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| IX | **附录** | | |
|
||
| 25 | [多模态网络（Multi-Modal Networks）、CLIP 与 VQGAN](./lessons/X-Extras/X1-MultiModal/README.md) | [Notebook](./lessons/X-Extras/X1-MultiModal/Clip.ipynb) | |
|
||
|
||
## 每课包含
|
||
|
||
* 课前阅读材料
|
||
* 可执行的 Jupyter Notebook，通常针对特定框架（**PyTorch** 或 **TensorFlow**）。可执行 notebook 也包含大量理论材料，因此要理解该主题，你需要至少完成其中一个版本的 notebook（PyTorch 或 TensorFlow 均可）。
|
||
* 部分主题提供 **Labs（实验）**，让你有机会将所学知识应用到具体问题中。
|
||
* 部分章节包含指向 [**MS Learn**](https://learn.microsoft.com/en-us/collections/7w28iy2xrqzdj0?WT.mc_id=academic-77998-bethanycheum) 相关主题模块的链接。
|
||
|
||
## 入门
|
||
|
||
### 🎯 刚接触 AI？从这里开始！
|
||
|
||
如果你完全不了解 AI，想要快速上手实践示例，请查看我们的 [**Beginner-Friendly Examples**](./examples/README.md)！其中包括：
|
||
|
||
- 🌟 **Hello AI World** - 你的第一个 AI 程序（模式识别）
|
||
- 🧠 **Simple Neural Network** - 从零构建神经网络
|
||
- 🖼️ **Image Classifier** - 对图像进行分类，附详细注释
|
||
- 💬 **Text Sentiment** - 分析文本的正负面情感
|
||
|
||
这些示例旨在帮助你在深入学习完整课程之前理解 AI 概念。
|
||
|
||
### 📚 完整课程设置
|
||
|
||
- 我们创建了[环境配置课程](./lessons/0-course-setup/setup.md)，帮助你搭建开发环境。教育工作者也可参考[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)
|
||
|
||
请按以下步骤操作：
|
||
|
||
Fork 仓库：点击本页面右上角的 "Fork" 按钮。
|
||
|
||
克隆仓库：`git clone https://github.com/microsoft/AI-For-Beginners.git`
|
||
|
||
别忘了给本仓库加星标（🌟），方便日后查找。
|
||
|
||
## 结识其他学习者
|
||
|
||
加入我们的[官方 AI Discord 服务器](https://aka.ms/genai-discord?WT.mc_id=academic-105485-bethanycheum)，与同修本课程的学习者交流、结识并获取支持。
|
||
|
||
如果在开发过程中有产品反馈或问题，请访问我们的 [Azure AI Foundry 开发者论坛](https://aka.ms/foundry/forum)
|
||
|
||
## 测验
|
||
|
||
> **关于测验的说明**：所有测验位于 etc\quiz-app 中的 Quiz-app 文件夹，或[在线访问](https://ff-quizzes.netlify.app/)。课程章节内也有链接；测验应用可在本地运行或部署到 Azure；请按照 `quiz-app` 文件夹中的说明操作。测验内容正在逐步本地化。
|
||
|
||
## 欢迎贡献
|
||
|
||
你有建议，或发现了拼写、代码错误？请提交 issue 或创建 pull request。
|
||
|
||
## 特别感谢
|
||
|
||
* **✍️ 主要作者：** [Dmitry Soshnikov](http://soshnikov.com), PhD
|
||
* **🔥 编辑：** [Jen Looper](https://twitter.com/jenlooper), PhD
|
||
* **🎨 手绘笔记插画师：** [Tomomi Imura](https://twitter.com/girlie_mac)
|
||
* **✅ 测验创作者：** [Lateefah Bello](https://github.com/CinnamonXI), [MLSA](https://studentambassadors.microsoft.com/)
|
||
* **🙏 核心贡献者：** [Evgenii Pishchik](https://github.com/Pe4enIks)
|
||
|
||
## 其他课程
|
||
|
||
我们的团队还制作了其他课程！欢迎查看：
|
||
|
||
<!-- CO-OP TRANSLATOR OTHER COURSES START -->
|
||
### 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)
|
||
|
||
---
|
||
|
||
### Generative AI Series
|
||
[](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)
|
||
|
||
---
|
||
|
||
### Core Learning
|
||
[](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 Series
|
||
[](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)
|
||
<!-- CO-OP TRANSLATOR OTHER COURSES END -->
|
||
|
||
## 获取帮助
|
||
|
||
如果你在构建 AI 应用时遇到困难或有任何疑问。欢迎与学习者及资深开发者一起讨论 MCP（Model Context Protocol）。这是一个互助社区，鼓励提问，并自由分享知识。
|
||
|
||
[](https://discord.gg/nTYy5BXMWG)
|
||
|
||
如果你在构建过程中有产品反馈或遇到错误，请访问：
|
||
|
||
[](https://aka.ms/foundry/forum)
|