Free Deep Learning Book (MIT Press)

The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free.

Source for picture: click here


Table of Contents



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

To access the book, click here.

Об авторе Лидия Пивоварова

СПбГУ - старший преподаватель, University of Helsinki - PhD student
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