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back to listing indexDeep Learning
[web search]Deep Learning
An MIT Press book
Ian Goodfellow, Yoshua Bengio and Aaron Courville
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. The print version will be available for sale soon. For up to date announcements, join our mailing list.
Citing the book
To cite this book, please use this bibtex entry:@unpublished{Goodfellow-et-al-2016-Book, title={Deep Learning}, author={Ian Goodfellow Yoshua Bengio and Aaron Courville}, note={Book in preparation for MIT Press}, url={http://www.deeplearningbook.org}, year={2016} }
FAQ
- Can I get a PDF of this book?
No, our contract with MIT Press forbids distribution of too easily copied electronic formats of the book.
- Why are you using HTML format for the drafts?
This format is a sort of weak DRM required by our contract with MIT Press. It's intended to discourage unauthorized copying/editing of the book.
- What is the best way to print the HTML format?
- When will the book come out?
It's difficult to predict. MIT Press is currently preparing the book for printing. Please contact us if you are interested in using the textbook for course materials in the short term; we will put you in contact with MIT Press.
Printing seems to work best printing directly from the browser, using Chrome. Other browsers do not work as well.
If you notice any typos (besides the known issues listed below) or have suggestions for exercises to add to the website, do not hesitate to contact any of the authors directly by e-mail: Ian (<lastname.firstname>@gmail.com), Yoshua (<firstname>.<lastname>@umontreal.ca), Aaron (<firstname>.<lastname>@gmail.com). The book itself is now complete and we are not currently making revisions beyond correcting any minor errors that remain.
Known issues: In outdated versions of the Edge browser, the "does not equal" sign sometimes appears as the "equals" sign. This may be resolved by updating to the latest version.
- 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