Deep Learning
FreeNeural networks & architectures (Goodfellow, Bengio, Courville).
FreeFree tier
About Deep Learning
Deep Learning is a comprehensive textbook by Ian Goodfellow, Yoshua Bengio, and Aaron Courville, published by MIT Press. It serves as a resource for students and practitioners entering machine learning and deep learning. The online version is available for free and covers fundamental applied math, modern practical deep networks, and deep learning research topics. The book includes exercises, lectures, and external links.
Key Features
Comprehensive coverage of deep learning fundamentals and research
Free online HTML version available
Exercises and lectures included
External resources and references
Authored by leading AI researchers
Pros & Cons
Pros
- Free online access to full book content
- Written by world-renowned experts in the field
- Covers both practical and theoretical aspects of deep learning
- Includes exercises to reinforce learning
Cons
- No official PDF version due to publisher DRM restrictions
- Some browsers (e.g., Edge) may have rendering issues with notation
- Not a software tool; purely an educational resource
Best For
Academic study of deep learningSelf-learning for practitioners entering machine learningReference for deep learning research
FAQ
Can I get a PDF of this book?
No, the contract with MIT Press forbids distribution of easily copied electronic formats. Only the online HTML version is available for free.
Why is the web version in HTML format?
The HTML format serves as a weak DRM required by the contract with MIT Press to discourage unauthorized copying and editing.
What is the best way to print the HTML version?
Printing works best using Chrome. Other browsers may not work as well.
Can I translate the book into other languages?
Translation rights have been purchased for Chinese by Posts and Telecom Press. For other languages, contact the publisher.