Generative Adversarial Networks with Python_Jason Brownlee.pdf

Generative Adversarial Networks with Python Deep Learning Generative Models for Image Synthesis and Image Translation Jason Brownlee i Disclaimer The information contained within this eBook is strictly for educational purposes. If you wish to apply ideas contained in this eBook, you are taking full responsibility for your actions. The author has made every effort to ensure the accuracy of the information within this book was correct at time of publication. The author does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. No part of this eBook may be reproduced or transmitted in any form or by anymeans, electronic or mechanical, recording or by any information storage and retrieval system,without written permission from the author. Acknowledgements Special thanks to my proofreader Sarah Martin and my technical editors Arun Koshy, Andrei Cheremskoy, and Michael Sanderson. Copyright Generative Adversarial Networks with Python ➞Copyright 2019 Jason Brownlee. All Rights Reserved. Edition: v1.5 Contents Copyright i Contents ii Preface iii Introductions v Welcome v I Foundations 1 1 What are Generative Adversarial Networks 3 1.1 Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 What Are Generative Models?. . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3 What Are Generative Adversarial Networks?. . . . . . . . . . . . . . . . . . . . 7 1.4 Why Generative Adversarial Networks?. . . . . . . . . . . . . . . . . . . . . . . 12 1.5 Further Reading. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 1.6 Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2 How to Develop Deep Learning Models With Keras 16 2.1 Tutorial Overview. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.2 Ker