Deep Learning MIT Press book -英文原版

这是英文版 MIT大学2016年最新出版的关于深度学习的书，之前还出过一个2015版的，2016版目前新增了不少内容，也修正了部分错误. 目录： Table of Contents Acknowledgements Notation 1 Introduction Part I: Applied Math and Machine Learning Basics 2 Linear Algebra 3 Probability and Information Theory 4 Numerical Computation 5 Machine Learning Basics Part II: Modern Practical Deep Networks 6 Deep Feedforward Networks 7 Regularization for Deep Learning 8 Optimization for Training Deep Models 9 Convolutional Networks 10 Sequence Modeling: Recurrent and Recursive Nets 11 Practical Methodology 12 Applications Part III: Deep Learning Research 13 Linear Factor Models 14 Autoencoders 15 Representation Learning 16 Structured Probabilistic Models for Deep Learning 17 Monte Carlo Methods 18 Confronting the Partition Function 19 Approximate Inference 20 Deep Generative Models Bibliography Index