{"id":19263030,"url":"https://github.com/datawhalechina/grape-book","last_synced_at":"2026-01-27T22:17:45.763Z","repository":{"id":103512162,"uuid":"550321348","full_name":"datawhalechina/grape-book","owner":"datawhalechina","description":"图深度学习（葡萄书），在线阅读地址： 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\"380\"\u003e\n\u003c/div\u003e\n\n## 葡萄书简介\n\n本教程主要基于京东团队的《图深度学习从理论到实践》，密西根州立大学的汤继良老师团队《图深度学习》，斯坦福大学 CS224W 图机器学习的内容进行整合，旨在帮助读者无痛入门图深度学习 。除了介绍深度学习和图基础知识以及经典图神经网络模型的理论外，我们还基于开源的图框架 NetworkX， DGL 和 PyG 提供了直接的上手代码。\n\n## 目录\n在线阅读地址：https://datawhalechina.github.io/grape-book\n\n| 章节 | 内容 |\n| :--- | :--- |\n| 第一章 | [介绍](https://datawhalechina.github.io/grape-book/#/docs/01%E4%BB%8B%E7%BB%8D/01%E4%BB%8B%E7%BB%8D) |  |\n| 第二章 | [图理论基础](https://datawhalechina.github.io/grape-book/#/docs\\02%E5%9B%BE%E7%90%86%E8%AE%BA%E5%9F%BA%E7%A1%80\\02%E5%9B%BE%E7%90%86%E8%AE%BA%E5%9F%BA%E7%A1%80) |\n| 第三章 | [深度学习基础](https://datawhalechina.github.io/grape-book/#/docs\\03%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E5%9F%BA%E7%A1%80\\03%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E5%9F%BA%E7%A1%80) |\n| 第四章 | [图表示学习](https://datawhalechina.github.io/grape-book/#/docs\\04%E5%9B%BE%E8%A1%A8%E7%A4%BA%E5%AD%A6%E4%B9%A0\\04%E5%9B%BE%E8%A1%A8%E7%A4%BA%E5%AD%A6%E4%B9%A0) |\n| 第五章 | [图卷积网络](https://datawhalechina.github.io/grape-book/#/docs\\05%E5%9B%BE%E5%8D%B7%E7%A7%AF%E7%BD%91%E7%BB%9C\\05%E5%9B%BE%E5%8D%B7%E7%A7%AF%E7%BD%91%E7%BB%9C) |\n| 第六章 | [关系图卷积神经网络](https://datawhalechina.github.io/grape-book/#/docs\\06%E5%85%B3%E7%B3%BB%E5%9B%BE%E5%8D%B7%E7%A7%AF%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C\\06%E5%85%B3%E7%B3%BB%E5%9B%BE%E5%8D%B7%E7%A7%AF%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C) |\n| 第七章 | [图注意力网络](https://datawhalechina.github.io/grape-book/#/docs\\07%E5%9B%BE%E6%B3%A8%E6%84%8F%E5%8A%9B%E7%BD%91%E7%BB%9C\\07%E5%9B%BE%E6%B3%A8%E6%84%8F%E5%8A%9B%E7%BD%91%E7%BB%9C) |\n| ... | ...|\n\n本书第一版包含第一到七章，涵盖了最常见的各类图神经网络理论和代码讲解。后续章节将包含图神经网络在各个领域内更加实际的应用案例。\n\n## 贡献者\n\n- [@小饭](https://github.com/xinqi-fan)：项目负责人，负责第一章介绍、第二章图理论基础、第四章图表示学习、及各章节校对\n- [@银晗](https://github.com/YinHan-Zhang)：负责第三章深度学习基础\n- [@洋](https://github.com/liu-yang-maker?tab=achievements)：负责第五章图卷积网络\n- [@汝超](https://github.com/rickyxume)：项目发起人，负责第六章关系图卷积神经网络\n- [@凯](https://github.com/HaSai666)：负责第七章图注意力网络\n\n\n## 参与贡献\n\n- 如果你想参与到项目中来欢迎提交 [Issue](https://github.com/datawhalechina/grape-book/issues) 申请开启一个新的章节，并在完成后进行 pull request。\n- 如果你发现了一些问题，欢迎在 [Issue](https://github.com/datawhalechina/grape-book/issues) 中进行反馈🐛。\n- 如果你对本项目感兴趣想要参与进来可以联系项目负责人[@小饭](https://github.com/xinqi-fan) 进行交流💬。\n\n如果你对 Datawhale 很感兴趣并想要发起一个新的项目，欢迎查看 [Datawhale 贡献指南](https://github.com/datawhalechina/DOPMC#%E4%B8%BA-datawhale-%E5%81%9A%E5%87%BA%E8%B4%A1%E7%8C%AE)。\n\n## 致谢\n本教程得到了《图深度学习从理论到实践》作者[姚博士](https://github.com/LuckBoyPhd/Resume)的肯定与支持，大家可以可以在[京东](https://item.jd.com/13167491.html )购买此书的纸质或电子版进行更加深入的学习！\n\n## 关注我们\n\u003cdiv align=center\u003e\n\u003cp\u003e扫描下方二维码关注公众号：Datawhale\u003c/p\u003e\n\u003cimg src=\"https://raw.githubusercontent.com/datawhalechina/pumpkin-book/master/res/qrcode.jpeg\" width = \"180\" height = \"180\"\u003e\n\u003c/div\u003e\n## LICENSE\n\u003ca rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-sa/4.0/\"\u003e\u003cimg 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