需要读的经典书籍和课程

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机器学习：

1.Gaussian Processes for Machine Learning

网址：http://www.gaussianprocess.org/gpml/ 带有code,
即: gpml toolbox

2.Bayesian Reasoning and Machine Learning. David Barber

网址：http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage 带code

即：BRMLtoolkit

注意版本号：已经更新到2016年了。

3.Machine Learning : A probabilistic Perspective
网址：http://www.cs.ubc.ca/~murphyk/MLbook/index.html

code : python and matlab https://github.com/probml
能下载到2012电子版

4.Pattern Recognition and Machine Learning.
含中文版
知乎：https://www.zhihu.com/question/20970802 [pattern recognition and machine learning这本书怎么看？]
代码地址：https://github.com/PRML/PRMLT

5.Understanding Machine Learning: From Theory to Algorithms 2014

6.The Element of Statistic Learning (2nd edition)
网址：https://statweb.stanford.edu/~tibs/ElemStatLearn/
R code: https://github.com/ajtulloch/Elements-of-Statistical-Learning

7.Probabilistic Graphical Models.pdf

8.All of Statistics.pdf

9.Learning from Data.pdf

10.Foundations of Machine Learning

优化：

1.Numerical Optimization ，Second Edition Jorge Nocedal Stephen J. Wright
2.Optimization Methods for Large-Scale Machine Learning L´eon Bottou，2016
**3.Convex Optimization**_Stephen Boyd–凸优化Boyd王书宁译

深度学习:

1.Convolutional Neural Networksfor Visual Recognition Feifei Li. 英文pdf ，中文： https://zhuanlan.zhihu.com/p/21930884
Feifei Li. 英文版涵盖了额外的：Training a Neural Network,Transfer Learning,etc.
2.Deep Learning ,Ian Goodfellow and Yoshua Bengio and Aaron Courville
英文网址: http://www.deeplearningbook.org/
中文网址: https://github.com/exacity/deeplearningbook-chinese
可以下载到中文pdf版

工具手册

1.The Matrix Cookbook.pdf
如果你对矢量范数的导数，迹的导数等不会求解，可以参看该手册。
2.Matrix Computations 4th edition

参考文献：

1.http://www.cnblogs.com/charlotte77/p/5488488.html [【机器学习Machine Learning】资料大全]

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