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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
深度学习入门教程, 优秀文章, Deep Learning Tutorial
| Date | Stars |
|---|---|
| 2026-07-24 | 17635 |
| 2026-07-25 | 17637 |
| 2026-07-28 | 17637 |
| 2026-07-30 | 17637 |
| 2026-07-31 | 17651 |
| 2026-08-06 | 17668 |
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# DeepLearning Tutorial ## 一. 入门资料 [**完备的 AI 学习路线，最详细的中英文资源整理**](https://zhuanlan.zhihu.com/p/64052743) :star: [AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NL](https://github.com/apachecn/AiLearning) [Machine-Learning](https://github.com/shunliz/Machine-Learning) ### 数学基础  * [矩阵微积分](https://zh.wikipedia.org/wiki/%E7%9F%A9%E9%98%B5%E5%BE%AE%E7%A7%AF%E5%88%86) * [机器学习的数学基础](https://github.com/fengdu78/Data-Science-Notes/tree/master/0.math/0.basic) * [CS229线性代数与概率论基础](https://github.com/fengdu78/Data-Science-Notes/tree/master/0.math/1.CS229) ### 机器学习基础 #### 快速入门 * [机器学习算法地图](http://www.tensorinfinity.com/paper_18.html) * [机器学习 吴恩达 Coursera个人笔记](https://github.com/Mikoto10032/DeepLearning/blob/master/books/%5BML-Coursera%5D%5B2014%5D%5BAndrew%20Ng%5D/%5B2014%5D%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E4%B8%AA%E4%BA%BA%E7%AC%94%E8%AE%B0%E5%AE%8C%E6%95%B4%E7%89%88v5.1.pdf) && [视频（含官方笔记）](https://www.coursera.org/learn/machine-learning) * [CS229 课程讲义中文翻译](https://kivy-cn.github.io/Stanford-CS-229-CN/#/) && [机器学习 吴恩达 cs229个人笔记](https://github.com/Mikoto10032/DeepLearning/blob/master/books/%5BML-CS229%5D%5B2011%5D%5BAndrew%20NG%5D/%5B2011%5D%E6%96%AF%E5%9D%A6%E7%A6%8F%E5%A4%A7%E5%AD%A6%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E8%AF%BE%E7%A8%8B%E4%B8%AA%E4%BA%BA%E7%AC%94.pdf) && [官网（笔记）](http://cs229.stanford.edu/) && [视频（中文字幕）](http://open.163.com/newview/movie/free?pid=M6SGF6VB4&mid=M6SGHFBMC) * [百页机器学习](http://themlbook.com/wiki/doku.php) #### 深入理解 * [《统计学习方法》李航](https://github.com/Mikoto10032/DeepLearning/tree/master/books/%E6%9D%8E%E8%88%AA-%E7%BB%9F%E8%AE%A1%E5%AD%A6%E4%B9%A0) && [《统计学习方法》各章节笔记](https://www.cnblogs.com/YongSun/tag/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/) && [《统计学习方法》各章节笔记](https://zhuanlan.zhihu.com/c_1213397558586257408) && [推荐答案：statistical-learning-method-solutions-manual](https://github.com/datawhalechina/statistical-learning-method-solutions-manual) [《统计学习方法》各章节笔记](https://www.cnblogs.com/liaohuiqiang/category/1039314.html) && [《统计学习方法》各章节代码实现与课后习题参考解答](https://blog.csdn.net/breeze_blows/article/details/85469944) * [《模式识别与机器学习》 Christopher Bishop](https://github.com/Mikoto10032/DeepLearning/blob/master/books/模式识别与机器学习PRML_Chinese_vision.pdf) * [《机器学习》 周志华](https://github.com/Mikoto10032/DeepLearning/blob/master/books/机器学习周志华.pdf) && [南瓜书：pumpkin-book](https://github.com/datawhalechina/pumpkin-book) * [《机器学习实战》 PelerHarrington](https://github.com/Mikoto10032/DeepLearning/blob/master/books/机器学习实战%20中文双页版.pdf) * [机器学习与深度学习书单](https://mp.weixin.qq.com/s?__biz=MzAxMjcyNjE5MQ==&mid=2650488718&idx=1&sn=815a79d27d500f0fb8db1fe1fc6cfe48&chksm=83a2e54eb4d56c58a0989654f920d64ad2784ce52e4b2bc6883974257cf475c9983f05fb88c1&scene=0&xtrack=1&ascene=14&devicetype=android-28&version=27000339&nettype=WIFI&abtest_cookie=AwABAAoACwATAAQAI5ceAFaZHgDQmR4A3JkeAAAA&lang=zh_CN&pass_ticket=oEB1108Pes6HkdxEITmBjTb2Glju5%2BEGqHZKz50fMg0rgK4l9Fodlbe%2FDm96iX57&wx_header=1) ### 深度学习基础 #### 快速入门 * [深度学习思维导图](https://github.com/dformoso/deeplearning-mindmap) && [深度学习算法地图](http://www.tensorinfinity.com/paper_158.html) * [《斯坦福大学深度学习基础教程》 Andrew Ng（吴恩达）](https://github.com/Mikoto10032/DeepLearning/blob/master/books/斯坦福大学-深度学习基础教程.pdf) * [深度学习 吴恩达 个人笔记](http://www.ai-start.com/dl2017/) && [视频](http://mooc.study.163.com/smartSpec/detail/1001319001.htm) * [MIT深度学习基础-2019视频课程](https://deeplearning.mit.edu/) * [台湾大学（NTU）李宏毅教授课程](http://speech.ee.ntu.edu.tw/~tlkagk/index.html) && [[leeml-notes](https://github.com/datawhalechina/leeml-notes) * [图解深度学习_Grokking-Deep-Learning](https://github.com/iamtrask/Grokking-Deep-Learning) * [《神经网络与深度学习》 Michael Nielsen](https://github.com/Mikoto10032/DeepLearning/blob/master/books/神经网络和深度学习neural%20networks%20and%20deep-learning-中文_ALL.pdf) * [ CS321-Hinton](http://www.cs.toronto.edu/~tijmen/csc321/) * [ CS230: Deep Learning](https://web.stanford.edu/class/cs230/) * [ CS294-112](http://rail.eecs.berkeley.edu/deeprlcourse/res
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:e9ccb1be66bbe696, topic:deep-learning, topic:pytorch, topic:tensorflow