Deep Learning with Python, Second Edition

ISBN: 1617296864

Author: Chollet, Francois

Condition: New

Printed in full color! Unlock the groundbreaking advances of deep learning with this extensively revised new edition of the bestselling original. Learn directly from the creator of Keras and master practical Python deep learning techniques that are easy to apply in the real world.In Deep Learning with Python, Second Edition you will learn:Deep learning from first principlesImage classification and image segmentationTimeseries forecastingText classification and machine translationText generation, neural style transfer, and image generationFull color printing throughoutDeep Learning with Python has taught thousands of readers how to put the full capabilities of deep learning into action. This extensively revised full color second edition introduces deep learning using Python and Keras, and is loaded with insights for both novice and experienced ML practitioners. Youll learn practical techniques that are easy to apply in the real world, and important theory for perfecting neural networks.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the technologyRecent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach-even if you have no background in mathematics or data science. This book shows you how to get started.About the bookDeep Learning with Python, Second Edition introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras creator Franois Chollet offers insights for both novice and experienced machine learning practitioners. As you move through this book, youll build your understanding through intuitive explanations, crisp color illustrations, and clear examples. Youll quickly pick up the skills you need to start developing deep-learning applications.What's insideDeep learning from first principlesImage classification and image segmentationTime series forecastingText classification and machine translationText generation, neural style transfer, and image generationFull color printing throughoutAbout the readerFor readers with intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required.About the authorFranois Chollet is a software engineer at Google and creator of the Keras deep-learning library.Table of Contents1 What is deep learning?2 The mathematical building blocks of neural networks3 Introduction to Keras and TensorFlow4 Getting started with neural networks: Classification and regression5 Fundamentals of machine learning6 The universal workflow of machine learning7 Working with Keras: A deep dive8 Introduction to deep learning for computer vision9 Advanced deep learning for computer vision10 Deep learning for timeseries11 Deep learning for text12 Generative deep learning13 Best practices for the real world14 Conclusions