《Deep Learning》网页版 An MIT Press book Ian Goodfellow and Yoshua Bengio and Aaron Courville Deep Learning Table of ContentsAcknowledgementsNotation1 IntroductionPart I: Applied Math and Machine Learning Basics2 Linear Algebra3 Probability and Information Theory4 Numerical Computation5 Machine Learning BasicsPart II: Modern Practical Deep Networks6 Deep Feedforward Networks7 Regularization for Deep Learning8 Optimization for Training Deep Models9 Convolutional Networks10 Sequence Modeling: Recurrent and Recursive Nets11 Practical Methodology12 ApplicationsPart III: Deep Learning Research13 Linear Factor Models14 Autoencoders15 Representation Learning16 Structured Probabilistic Models for Deep Learning17 Monte Carlo Methods18 Confronting the Partition Function19 Approximate Inference20 Deep Generative ModelsBibliographyIndex Post Views: 699 作者: 公子小白 SOS团团员,非外星人、未来人、超能力者。。。 查看公子小白的所有文章