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Deep Learning with Python, Second Edition

Fran?ois Chollet
  • MEAP began March 2020
  • Publication in Fall 2021 (estimated)
  • ISBN 9781617296864
  • 400 pages (estimated)
  • printed in black & white
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The first edition of Deep Learning with Python is one of the best books on the subject. The second edition made it even better.

Todd Cook
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The bestseller revised! Deep Learning with Python, Second Edition is a comprehensive introduction to the field of deep learning using Python and the powerful Keras library. Written by Google AI researcher Fran?ois Chollet, the creator of Keras, this revised edition has been updated with new chapters, new tools, and cutting-edge techniques drawn from the latest research. You’ll build your understanding through practical examples and intuitive explanations that make the complexities of deep learning accessible and understandable.

about the technology

Machine learning has made remarkable progress in recent years. We’ve gone from near-unusable speech recognition, to near-human accuracy. From machines that couldn't beat a serious Go player, to defeating a world champion. Medical imaging diagnostics, weather forecasting, and natural language question answering have suddenly become tractable problems. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications across every industry sector

about the book

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. You’ll learn directly from the creator of Keras, Fran?ois Chollet, building your understanding through intuitive explanations and practical examples. Updated from the original bestseller with over 50% new content, this second edition includes new chapters, cutting-edge innovations, and coverage of the very latest deep learning tools. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.

what's inside

  • Deep learning from first principles
  • Image-classification, imagine segmentation, and object detection
  • Deep learning for natural language processing
  • Timeseries forecasting
  • Neural style transfer, text generation, and image generation

about the reader

Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required.

about the author

Fran?ois Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does AI research, with a focus on abstraction and reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.

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Really easy to read and gives practical examples and easy to understand explanations of the concepts behind deep learning.

Billy O'Callaghan

A tell-tale book that tells you all the secrets of deep learning!

Nikos Kanakaris

A great refresher of the old concepts explored in new and exciting ways. Manifold hypothesis steals the show!

Sayak Paul

One of the best books on this topic.

Rauhsan Jha

The book is full of insights, useful both for the novice and the more experienced machine learning professional.

Viton Vitanis

This is the book to read if you want to learn DL.

Kjell Jansson

Francois explains everything in a very lucid & systematic manner, this approach of writing certainly gives confidence in users.

Rauhsan Jha
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