DEEP LEARNING

DEEP LEARNING

An MIT Press book in preparation

Yoshua Bengio, Ian Goodfellow and Aaron Courville

Citing the book in preparation

If you want to cite this book in preparation, please use the following bibtex entry:

@unpublished{Bengio-et-al-2014-Book,
    title={Deep Learning},
    author={Yoshua Bengio and Ian J. Goodfellow and Aaron Courville},
    note={Book in preparation for MIT Press},
    url={http://www.iro./~bengioy/dlbook},
    year={2014}
}

Draft chapters available for feedback - Version 01/01/2015

Please help us make this a great book! This draft is still full of typos and can be improved in many ways. Your suggestions are more than welcome. Do not hesitate to contact any of the authors directly by e-mail or Google+ messages: Yoshua, Ian, Aaron.
NOTE: SEVERAL PEOPLE HAVE REPORTED THAT PRINTING WORKS BETTER FROM THE CHROME BROWSER.
Warning: we are in the midst of an overhaul of the notation.

• Table of Contents
• Deep Learning for AI
• Linear Algebra
• Probability and Information Theory
• Numerical Computation
• Machine Learning Basics
• Feedforward Deep Networks
• Numerical Optimization
• Structured Probabilistic Models: A Deep Learning Perspective
• Unsupervised and Transfer Learning
• (NEW)Distributed Representations: Disentangling the Underlying Factors
• Convolutional Networks
• Sequence Modeling: Recurrent and Recursive Nets
• The Manifold Perspective on Auto-Encoders
• Confronting the Partition Function
• References