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Title: GitHub - qiy/DeepLearning: 深度学习笔记

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https://patch-diff.githubusercontent.com/qiy/DeepLearning#deeplearning
https://patch-diff.githubusercontent.com/qiy/DeepLearning#入门资料
1. 《机器学习》 周志华https://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%91%A8%E5%BF%97%E5%8D%8E.pdf
2. 《深度学习》 Yoshua+Bengio+Ian+GoodFellowhttps://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0.DeepLearning.Yoshua%2BBengio%2BIan%2BGoodFellow%E4%B8%AD%E6%96%87%E7%89%88.pdf
3. 《神经网络与深度学习》 Michael Nielsenhttps://github.com/Mikoto10032/DeepLearning/blob/master/books/%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C%E5%92%8C%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0neural%20networks%20and%20deep-learning-%E4%B8%AD%E6%96%87_ALL.pdf
4. 《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/%E6%96%AF%E5%9D%A6%E7%A6%8F%E5%A4%A7%E5%AD%A6-%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E5%9F%BA%E7%A1%80%E6%95%99%E7%A8%8B.pdf
5. 《模式识别与机器学习》 Christopher Bishophttps://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%A8%A1%E5%BC%8F%E8%AF%86%E5%88%AB%E4%B8%8E%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0PRML_Chinese_vision.pdf
6. 《Tensorflow实战Google深度学习框架》 郑泽宇 顾思宇https://github.com/Mikoto10032/DeepLearning/blob/master/books/Tensorflow%20%E5%AE%9E%E6%88%98Google%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E6%A1%86%E6%9E%B6.pdf
7. 《机器学习实战》 PelerHarringtonhttps://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%AE%9E%E6%88%98%20%E4%B8%AD%E6%96%87%E5%8F%8C%E9%A1%B5%E7%89%88.pdf
8. 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/special/opencourse/machinelearning.html
9. 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
10. 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
11. 深度学习 李飞飞 已授权个人翻译笔记https://zhuanlan.zhihu.com/p/21930884
视频http://study.163.com/course/courseMain.htm?courseId=1003223001
12. 台湾大学（NTU）李宏毅教授课程http://speech.ee.ntu.edu.tw/~tlkagk/index.html
https://patch-diff.githubusercontent.com/qiy/DeepLearning#神经网络模型概览
1. 一文看懂25个神经网络模型https://blog.csdn.net/qq_35082030/article/details/73368962
2. DNN概述论文：详解前馈、卷积和循环神经网络技术https://zhuanlan.zhihu.com/p/29141828
3. colah's bloghttp://colah.github.io/
https://patch-diff.githubusercontent.com/qiy/DeepLearning#cnn
1. 94页论文综述卷积神经网络：从基础技术到研究前景https://zhuanlan.zhihu.com/p/35388569
2. 从LeNet-5到DenseNethttps://zhuanlan.zhihu.com/p/31006686
3. CNN变体：图像分类神经网络https://zhuanlan.zhihu.com/p/35688103
4. CNN图像分割简史：从R-CNN到Mask R-CNN（译）https://zhuanlan.zhihu.com/p/26652657
5. 变形卷积核、可分离卷积https://zhuanlan.zhihu.com/p/28749411
https://patch-diff.githubusercontent.com/qiy/DeepLearning#gan
1. GAN原理学习笔记https://zhuanlan.zhihu.com/p/27295635
2. GAN学习指南：从原理入门到制作生成Demohttps://zhuanlan.zhihu.com/p/24767059
3. 机器之心GitHub项目：GAN完整理论推导与实现https://zhuanlan.zhihu.com/p/29837245
4. 极端图像压缩的对抗生成网络https://zhuanlan.zhihu.com/p/35783437?group_id=969598777652420608
5. 千奇百怪的GAN变体https://zhuanlan.zhihu.com/p/26491601
6. 台湾大学李宏毅GAN教程https://www.youtube.com/watch?v=0CKeqXl5IY0&feature=youtu.be
Basichttps://github.com/Mikoto10032/DeepLearning/blob/master/books/GAN-Basic%20Idea%20(2017.04.21).pdf
Improvinghttps://github.com/Mikoto10032/DeepLearning/blob/master/books/GAN-Improving%20GAN%20(2017.05.05).pdf
https://patch-diff.githubusercontent.com/qiy/DeepLearning#rnn---
完全图解RNN、RNN变体、Seq2Seq、Attention机制https://zhuanlan.zhihu.com/p/28054589
https://patch-diff.githubusercontent.com/qiy/DeepLearning#lstm-
1. （译）理解长短期记忆(LSTM) 神经网络https://zhuanlan.zhihu.com/p/24018768
2. 一文读懂LSTM和RNNhttps://zhuanlan.zhihu.com/p/35878575?group_id=970350175025385472
3. 探索LSTM：基本概念到内部结构https://zhuanlan.zhihu.com/p/27345523
4. 翻译：深入理解LSTM系列https://patch-diff.githubusercontent.com/qiy/DeepLearning/blob/master
深入理解 LSTM 网络 (一)https://blog.csdn.net/matrix_space/article/details/53374040
深入理解 LSTM 网络 (二)https://blog.csdn.net/matrix_space/article/details/53376870
https://patch-diff.githubusercontent.com/qiy/DeepLearning#前沿神经网络--
https://patch-diff.githubusercontent.com/qiy/DeepLearning#resnet深度残差网络------
一文简述ResNet及其多种变体https://zhuanlan.zhihu.com/p/35985680?group_id=971491939699388416
ResNet解析https://blog.csdn.net/lanran2/article/details/79057994
https://patch-diff.githubusercontent.com/qiy/DeepLearning#capsnet胶囊网络--
1. 先读懂CapsNet架构然后用TensorFlow实现https://zhuanlan.zhihu.com/p/30753326
2. CapsNet入门系列http://mp.weixin.qq.com/s?__biz=MzI3ODkxODU3Mg==&mid=2247484099&idx=1&sn=97e209f1a9860c8d8c51e81d98fc8a0a&chksm=eb4ee600dc396f16624a33cdfc0ead905e62ae9447b49b20146020e6cbd7d71f089101512a40&scene=21#wechat_redirect
CapsNet入门系列之一：胶囊网络背后的直觉http://mp.weixin.qq.com/s?__biz=MzI3ODkxODU3Mg==&mid=2247484099&idx=1&sn=97e209f1a9860c8d8c51e81d98fc8a0a&chksm=eb4ee600dc396f16624a33cdfc0ead905e62ae9447b49b20146020e6cbd7d71f089101512a40&scene=21#wechat_redirect
CapsNet入门系列之二：胶囊如何工作http://mp.weixin.qq.com/s?__biz=MzI3ODkxODU3Mg==&mid=2247484165&idx=1&sn=0ca679e3a5f499f8d8addb405fe3df83&chksm=eb4ee7c6dc396ed0a330fcac12690110bcaf9a8a10794dbc5e1a326c69ecbb140140f55fd6ba&scene=21#wechat_redirect
CapsNet入门系列之三：囊间动态路由算法http://mp.weixin.qq.com/s?__biz=MzI3ODkxODU3Mg==&mid=2247484433&idx=1&sn=3afe4605bc2501eebbc41c6dd1af9572&chksm=eb4ee0d2dc3969c4619d6c1097d5c949c76c6c854e60d36eba4388da2c3855747818d062c90a&scene=21#wechat_redirect
CapsNet入门系列之四：胶囊网络架构https://mp.weixin.qq.com/s/6CRSen8P6zKaMGtX8IRfqw
https://patch-diff.githubusercontent.com/qiy/DeepLearning#yoloyou-only-look-once目标检测模型-
目标检测模型YOLO v3问世https://zhuanlan.zhihu.com/p/34995629
目标检测|YOLOv2原理与实现(附YOLOv3)https://zhuanlan.zhihu.com/p/35325884?group_id=966229905398362112
https://patch-diff.githubusercontent.com/qiy/DeepLearning#优化算法--
1. 优化算法纵览http://fa.bianp.net/teaching/2018/eecs227at/
2. 从梯度下降到Adamhttps://zhuanlan.zhihu.com/p/27449596
3. 从梯度下降到拟牛顿法：盘点训练神经网络的五大学习算法https://zhuanlan.zhihu.com/p/25703402
4. 正则化技术总结https://zhuanlan.zhihu.com/p/35429054?group_id=966442942538444800
1. [视频讲解]史上最全面的正则化技术总结与分析--part1https://zhuanlan.zhihu.com/p/35429054?group_id=966442942538444800
2. [视频讲解]史上最全面的正则化技术总结与分析--part2https://zhuanlan.zhihu.com/p/35432128?group_id=966443101011738624
5. 最优化算法系列（math）https://blog.csdn.net/chunyun0716/article/category/6188191/2
6. 神经网络训练中的梯度消失与梯度爆炸https://zhuanlan.zhihu.com/p/25631496
7. 神经网络的优化及训练https://zhuanlan.zhihu.com/p/36050743
https://patch-diff.githubusercontent.com/qiy/DeepLearning#机器学习基础理论--
https://patch-diff.githubusercontent.com/qiy/DeepLearning#信息论
1. 机器学习中的各种熵https://zhuanlan.zhihu.com/p/35423404
2. 从香农熵到手推KL散度：纵览机器学习中的信息论https://zhuanlan.zhihu.com/p/32985487
https://patch-diff.githubusercontent.com/qiy/DeepLearning#深度学习相关算法--
https://patch-diff.githubusercontent.com/qiy/DeepLearning#svd
1. 关于奇异值分解SVD的总结（PCA、LDI）https://zhuanlan.zhihu.com/p/30482640
2. 奇异值分解（SVD）https://zhuanlan.zhihu.com/p/29846048
3. 奇异值分解(SVD)原理详解及推导https://blog.csdn.net/zhongkejingwang/article/details/43053513
4. SVD在推荐系统中的应用详解以及算法推导https://blog.csdn.net/zhongkejingwang/article/details/43083603
https://patch-diff.githubusercontent.com/qiy/DeepLearning#迁移学习
1. 迁移学习：经典算法解析https://blog.csdn.net/linolzhang/article/details/73358219
2. 什么是迁移学习 (Transfer Learning)？这个领域历史发展前景如何？https://www.zhihu.com/question/41979241
3. 迁移学习个人笔记https://github.com/Mikoto10032/DeepLearning/blob/master/notes/%E6%97%A5%E5%B8%B8%E9%98%85%E8%AF%BB%E7%AC%94%E8%AE%B0/2018_4_12_%E8%BF%81%E7%A7%BB%E5%AD%A6%E4%B9%A0.pdf
https://patch-diff.githubusercontent.com/qiy/DeepLearning#元学习
OpenAI提出新型元学习方法EPG，调整损失函数实现新任务上的快速训练https://zhuanlan.zhihu.com/p/35869158?group_id=970310501209645056
https://patch-diff.githubusercontent.com/qiy/DeepLearning#强化学习
强化学习（Reinforcement Learning）知识整理https://zhuanlan.zhihu.com/p/25498081
强化学习从入门到放弃的资料https://zhuanlan.zhihu.com/p/34918639
强化学习入门https://zhuanlan.zhihu.com/p/25498081
强化学习入门 第一讲 MDPhttps://zhuanlan.zhihu.com/p/25498081
https://patch-diff.githubusercontent.com/qiy/DeepLearning#推荐算法
推荐算法相关的文档整理https://zhuanlan.zhihu.com/p/29969721
https://patch-diff.githubusercontent.com/qiy/DeepLearning#机器学习相关算法
https://patch-diff.githubusercontent.com/qiy/DeepLearning#决策树decision-tree---
Python3《机器学习实战》学习笔记（二）：决策树基础篇之让我们从相亲说起https://blog.csdn.net/c406495762/article/details/75663451
Python3《机器学习实战》学习笔记（三）：决策树实战篇之为自己配个隐形眼镜https://blog.csdn.net/c406495762/article/details/76262487
机器学习实战教程（十三）：树回归基础篇之CART算法与树剪枝http://cuijiahua.com/blog/2017/12/ml_13_regtree_1.html
《机器学习实战》基于信息论的三种决策树算法(ID3,C4.5,CART)https://blog.csdn.net/gamer_gyt/article/details/51242815
说说决策树剪枝算法https://zhuanlan.zhihu.com/p/31404571
机器学习实战 第九章 树回归https://blog.csdn.net/namelessml/article/details/52595066
https://patch-diff.githubusercontent.com/qiy/DeepLearning#支持向量机svm--
SVM通俗导论 July（本文章是我看过最好的SVM导论）https://github.com/Mikoto10032/DeepLearning/blob/master/books/%E6%94%AF%E6%8C%81%E5%90%91%E9%87%8F%E6%9C%BA%E9%80%9A%E4%BF%97%E5%AF%BC%E8%AE%BA%EF%BC%88%E7%90%86%E8%A7%A3SVM%E7%9A%84%E4%B8%89%E5%B1%82%E5%A2%83%E7%95%8C%EF%BC%89LaTeX%E6%9C%80%E6%96%B0%E7%89%88_2015.1.9.pdf
Python3《机器学习实战》学习笔记（八）：支持向量机原理篇之手撕线性SVM （SMO训练过程总结得清晰易懂）https://blog.csdn.net/c406495762/article/details/78072313
svm核函数的理解和选择https://blog.csdn.net/leonis_v/article/details/50688766
SVM核函数https://blog.csdn.net/xiaowei_cqu/article/details/35993729
https://patch-diff.githubusercontent.com/qiy/DeepLearning#标签传播算法label-propagation
标签传播算法（Label Propagation）及Python实现https://blog.csdn.net/zouxy09/article/details/49105265
参考资料https://github.com/Mikoto10032/DeepLearning/blob/master/books/Semi-Supervised%20Learning%20with%20Graphs.pdf
https://patch-diff.githubusercontent.com/qiy/DeepLearning#工具平台使用-
https://patch-diff.githubusercontent.com/qiy/DeepLearning#tensorflow
【干货】史上最全的Tensorflow学习资源汇总https://zhuanlan.zhihu.com/p/35515805?group_id=967136289941897216
《21个项目玩转深度学习———基于TensorFlow的实践详解》https://github.com/hzy46/Deep-Learning-21-Examples
https://patch-diff.githubusercontent.com/qiy/DeepLearning#mxnet
Gluonhttps://github.com/Mikoto10032/DeepLearning/blob/master/books/gluon_tutorials_zh%EF%BC%88%E5%9F%BA%E4%BA%8EMXNet%EF%BC%89.pdf
https://patch-diff.githubusercontent.com/qiy/DeepLearning#python3x
廖雪峰Python教程https://www.liaoxuefeng.com/wiki/0014316089557264a6b348958f449949df42a6d3a2e542c000
菜鸟教程http://www.runoob.com/python3/python3-tutorial.html
https://patch-diff.githubusercontent.com/qiy/DeepLearning#数据集-
1. 25个深度学习相关公开数据集https://zhuanlan.zhihu.com/p/35449783
https://patch-diff.githubusercontent.com/qiy/DeepLearning#to-do-list
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