资源|5本深度学习和10本机器学习书籍(免费下载)

5本深度学习书籍资源推荐

深度学习(Deep Learning)byIan Goodfellow and Yoshua Bengio and Aaron Courville

中文版下载地址:https://github.com/exacity/deeplearningbook-chinese

R语言深度学习实践指南(Deep Learning Made Easy with R)by Dr. N.D. Lewis

下载地址:http://download.csdn.net/detail/oscer2016/9829915

深度学习基础(Fundamentals of Deep Learning)by Nikhil Buduma

下载地址:http://www.taodocs.com/p-32598980.html

神经网络和统计学习(Neural networks and statistical learning)by K.-L. Du and M.N.s. Swamy

下载地址:http://download.csdn.net/detail/oscer2016/9829919

神经网络和深度学习(Neural Networks and Deep Learning)by Michael Niels

下载地址:http://download.csdn.net/download/newhotter/9651111

10本机器学习书籍资源推荐

机器学习、神经网络和统计分类(Machine Learning, Neural Networks, and Statistical Classification)by

D. Michie, D.J. Spiegelhalter, C.C. Taylor

下载地址:http://www1.maths.leeds.ac.uk/~charles/statlog/

贝叶斯推理和机器学习(Bayesian Reasoning and Machine Learning)by David Barber

下载地址:http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.Online

机器学习的高斯过程(Gaussian Processes for Machine Learning)by Carl Edward Rasmussen and Christopher K. I. Williams,The MIT Press

下载地址:http://www.gaussianprocess.org/gpml/

信息理论、推理和学习算法(Information Theory, Inference, and Learning Algorithms)by David J.C. MacKay

下载地址:http://www.inference.phy.cam.ac.uk/mackay/itprnn/book.html

统计学习元素(The Elements of Statistical Learning)by Trevor Hastie, Robert Tibshirani, Jerome Friedman

下载地址:http://statweb.stanford.edu/~tibs/ElemStatLearn/printings/ESLII_print10.pdf

机器学习课程(A Course in Machine Learning)by Hal Daumé III

下载地址:http://ciml.info/

机器学习导论(Introduction to Machine Learning)by Amnon Shashua,Cornell University

下载地址:https://arxiv.org/abs/0904.3664v1

强化学习(Reinforcement Learning)

下载地址:https://www.intechopen.com/books/reinforcement_learning

机器学习导论(Introduction to Machine Learning)- By Nils Nilsson

下载地址:http://ai.stanford.edu/~nilsson/mlbook.html

强化学习(Reinforcement Learning)- MIT Press

下载地址:http://webdocs.cs.ualberta.ca/~sutton/book/the-book.html

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