• Title Deep Learning with Python, Second Edition
• Author(s) Francois Chollet
• Publisher: Manning; 2nd edition (December 21, 2021)
• Permission: Free to read entire book online by the publisher (Manning), with limited time every day.
• Hardcover/Paperback 504 pages (First Edition: 384 pages)
• eBook HTML
• Language: English
• ISBN-10/ASIN: 1617296864 (First Edition: 1617294438)
• ISBN-13: 978-1617296864 (First Edition: 978-1617294433)
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Book Description

This book introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator François Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, you'll build your understanding through intuitive explanations, crisp color illustrations, and clear examples. You'll quickly pick up the skills you need to start developing deep-learning applications.

• Deep learning from first principles
• Image classification and image segmentation
• Timeseries forecasting
• Text classification and machine translation
• Text generation, neural style transfer, and image generation
• Full color printing throughout

The Book is for readers with intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required.

• Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural networks since 2012. Francois is currently doing deep learning research at Google. He blogs about deep learning at blog.keras.io.

• Amazon
• Amazon (The First Edition)

• Deep Learning and Neural Networks
• Python Programming
• Machine Learning
• Artificial Intelligence
• Data Analysis and Data Mining

• Deep Learning with Python, 2nd Edition (Francois Chollet)
• The First Edition
• The Booke Homepage (Sample Capters, Source Code, etc.)

• Deep Learning with PyTorch (Eli Stevens, et al)
• Python Machine Learning Projects (Brian Boucheron, et al)
• Deep Learning with JavaScript: Neural Networks in TensorFlow.js
• Deep Learning and the Game of Go (Max Pumperla, et al)