└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # Courses 2 | * 吴恩达CS230深度学习 3 | 4 | 秋季CS230视频列表： 5 | [https://www.bilibili.com/video/av47055599](https://www.bilibili.com/video/av47055599) 6 | 7 | 8 | 春季CS230课程大纲： 9 | [http://cs230.stanford.edu/syllabus/](http://cs230.stanford.edu/syllabus/) 10 | 11 | 12 | Cheetsheet（斯坦福助教给出）： 13 | [https://stanford.edu/~shervine/teaching/cs-230.html](https://stanford.edu/~shervine/teaching/cs-230.html) 14 | 15 | 16 | # e-book 17 | 18 | * 复旦教授邱锡鹏开源发布《神经网络与深度学习》 19 | 20 | [https://nndl.github.io/](https://nndl.github.io/) 21 | 22 | * 南瓜书 23 | 24 | 《pumpkin-book》GitHub项目链接： 25 | [https://github.com/datawhalechina/pumpkin-book](https://github.com/datawhalechina/pumpkin-book) 26 | 27 | 在线阅读地址： 28 | [https://datawhalechina.github.io/pumpkin-book/](https://datawhalechina.github.io/pumpkin-book/) 29 | 30 | * 周志华新书《演化学习：理论和算法的进展》 31 | 32 | [https://www.springer.com/cn/book/9789811359552](https://www.springer.com/cn/book/9789811359552) 33 | 34 | * 《深度学习理论与实战：提高篇》 35 | 36 | 37 | [http://fancyerii.github.io/2019/03/14/dl-book/](http://fancyerii.github.io/2019/03/14/dl-book/) 38 | 39 | * 《动手学深度学习》，英文版即伯克利深度学习（STAT 157，2019春）教材 40 | 41 | [https://github.com/d2l-ai/d2l-zh](https://github.com/d2l-ai/d2l-zh) 42 | 43 | [http://zh.gluon.ai/index.html](http://zh.gluon.ai/index.html) 44 | 45 | [https://zh.d2l.ai/index.html](https://zh.d2l.ai/index.html) 46 | 47 | * Convex Optimization 凸优化 48 | 49 | [https://web.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf](https://web.stanford.edu/~boyd/cvxbook/bv_cvxbook.pdf) 50 | 51 | * 《AI 算法工程师手册》 52 | 53 | 54 | [www.huaxiaozhuan.com/](http://www.huaxiaozhuan.com/) 55 | 56 | * 《沉浸式线性代数》，全交互式体验 57 | 58 | [http://immersivemath.com/ila/index.html](http://immersivemath.com/ila/index.html) 59 | 60 | # Tutorial 61 | * 数据清洗&预处理入门完整指南 62 | 63 | [https://towardsdatascience.com/the-complete-beginners-guide-to-data-cleaning-and-preprocessing-2070b7d4c6d](https://towardsdatascience.com/the-complete-beginners-guide-to-data-cleaning-and-preprocessing-2070b7d4c6d) 64 | 65 | * 机器学习成才之路：这是一条GitHub高赞的学习路径 66 | 67 | [https://github.com/clone95/Machine-Learning-Study-Path-March-2019](https://github.com/clone95/Machine-Learning-Study-Path-March-2019) 68 | 69 | 70 | * 标星 1w 的机器学习资源：中文版路线图、视频、电子书 71 | 72 | [https://github.com/apachecn/AiLearning](https://github.com/apachecn/AiLearning) 73 | 74 | * PyTorch 超全资源列表 75 | 76 | [https://github.com/bharathgs/Awesome-pytorch-list](https://github.com/bharathgs/Awesome-pytorch-list) 77 | 78 | * Google机器学习速成课程(使用Tensorflow API) 79 | 80 | [https://developers.google.com/machine-learning/crash-course/](https://developers.google.com/machine-learning/crash-course/) 81 | 82 | * 关于深度学习优化器 optimizer 的选择，你需要了解这些 83 | 84 | [https://www.leiphone.com/news/201706/e0PuNeEzaXWsMPZX.html](https://www.leiphone.com/news/201706/e0PuNeEzaXWsMPZX.html) 85 | 86 | * 布朗计算机教授牵头设计，用交互动画学习人工智能 87 | 88 | [https://okai.brown.edu/zh/index.html](https://okai.brown.edu/zh/index.html) 89 | 90 | * [deeplizard]非常容易理解的PyTorch教程,五星好评 91 | 92 | [http://deeplizard.com/learn/video/v5cngxo4mIg](http://deeplizard.com/learn/video/v5cngxo4mIg) 93 | # Useful Resources 94 | * GitHub万星的ML算法面试大全 95 | 96 | [https://github.com/imhuay/Algorithm_Interview_Notes-Chinese](https://github.com/imhuay/Algorithm_Interview_Notes-Chinese) 97 | 98 | * 《算法导论》第三版习题答案 99 | 100 | [https://github.com/walkccc/CLRS](https://github.com/walkccc/CLRS) 101 | 102 | * GitHub 上读北大：覆盖 AI 高数等 100 多门课 103 | 104 | 105 | “北大图书馆”Github传送门： 106 | [https://github.com/lib-pku/libpku](https://github.com/lib-pku/libpku) 107 | 108 | 109 | 浙大项目传送门： 110 | [https://github.com/QSCTech/zju-icicles](https://github.com/QSCTech/zju-icicles) 111 | 112 | 清华大学共享了计算机系课程资源： 113 | [https://github.com/Trinkle23897/thu-cst-cracker](https://github.com/Trinkle23897/thu-cst-cracker) 114 | 115 | 中科大共享了计算机学院的课程资源： 116 | [https://github.com/USTC-Resource/USTC-Course](https://github.com/USTC-Resource/USTC-Course) 117 | 118 | 上海交大共享了14门关于计算机和高数的课程资源： 119 | [https://github.com/CoolPhilChen/SJTU-Courses/](https://github.com/CoolPhilChen/SJTU-Courses/) 120 | 121 | * 欲学机器学习必先掌握Shell，AI工程师自制教程 | PDF+视频 122 | 123 | [https://zhuanlan.zhihu.com/p/63405398](https://zhuanlan.zhihu.com/p/63405398) 124 | 125 | * 机器学习术语表 126 | 127 | [https://developers.google.com/machine-learning/glossary/#top_of_page](https://developers.google.com/machine-learning/glossary/#top_of_page) 128 | 129 | * GitHub：深度学习最全资料集锦 130 | 131 | [https://zhuanlan.zhihu.com/p/64361703?utm_source=wechat_session&utm_medium=social&utm_oi=772887009306906624&from=groupmessage&s_s_i=%2FTyb75cIhNIgxcLXu1sVl2SyvnIOPwX%2BWzIx3PFAjAE%3D&s_r=1](https://zhuanlan.zhihu.com/p/64361703?utm_source=wechat_session&utm_medium=social&utm_oi=772887009306906624&from=groupmessage&s_s_i=%2FTyb75cIhNIgxcLXu1sVl2SyvnIOPwX%2BWzIx3PFAjAE%3D&s_r=1) 132 | 133 | * 通天塔|论文阅读平台 134 | 135 | [http://tongtianta.site/](http://tongtianta.site/) 136 | 137 | # Coursera Course 138 | 139 | #Articles 140 | * Dropout: A Simple Way to Prevent Neural Networks from 141 | Overfitting 142 | 143 | [http://jmlr.org/papers/volume15/srivastava14a.old/srivastava14a.pdf](http://jmlr.org/papers/volume15/srivastava14a.old/srivastava14a.pdf) 144 | 145 | * An overview of gradient descent optimization algorithms 146 | 147 | [https://arxiv.org/pdf/1609.04747.pdf](https://arxiv.org/pdf/1609.04747.pdf) 148 | 149 | 中文解析： 150 | [https://cloud.tencent.com/developer/article/1012229](https://cloud.tencent.com/developer/article/1012229) 151 | 152 | 153 | * Adagrad 154 | 155 | [Adaptive Subgradient Methods for 156 | Online Learning and Stochastic Optimization](http://202.117.4.101/cache/3/03/www.jmlr.org/e34d2a85690703a4fe23fad51c6cac1a/duchi11a.pdf) 157 | 158 | * Review of Deep Learning Algorithms and Architectures 159 | 160 | [https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8694781&tag=1](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8694781&tag=1) 161 | 162 | #Blog 163 | * SJTU PhD 164 | 165 | [https://me.csdn.net/u014636245](https://me.csdn.net/u014636245) 166 | 167 | # Python的那些坑 168 | * Python - 100天从新手到大师 169 | 170 | [https://github.com/jackfrued/Python-100-Days](https://github.com/jackfrued/Python-100-Days) 171 | 172 | * Python语法基础——关于全局变量与局部变量 173 | 174 | [https://blog.csdn.net/dongtingzhizi/article/details/8973569](https://blog.csdn.net/dongtingzhizi/article/details/8973569) 175 | --------------------------------------------------------------------------------