Deep Learning with Python you own this product

François Chollet
  • November 2017
  • ISBN 9781617294433
  • 384 pages

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Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples.

This book is one of three products included in the Getting Started with Deep Learning bundle. Get the entire bundle for only $59.99.

about the technology

Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications.

about the book

Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. 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
  • Setting up your own deep-learning environment
  • Image-classification models
  • Deep learning for text and sequences
  • 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

François 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 deep-learning research, with a focus on computer vision and the application of machine learning to formal 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.

The clearest explanation of deep learning I have come across...it was a joy to read.

Richard Tobias, Cephasonics

An excellent hands-on introductory title, with great depth and breadth.

David Blumenthal-Barby, Babbel

Bridges the gap between the hype and a functioning deep-learning system.

Peter Rabinovitch, Akamai

The best resource for becoming a master of Keras and deep learning.

Claudio Rodriguez, Cox Media Group

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