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Deep Learning for Dummies.pdf
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Deep Learning for Dummies When you work through Deep Learning For Dummies, you gain access to a lot of example code that will run on a standard Mac, Linux, or Windows system. You can also run the code online using something like Google Colab. (We provide pointers on how to get the information you need to do this.) Special equipment, such as a GPU, will make the examples run faster. However, the point of this book is that you can create deep learning code no matter what sort of machine you have as long as you’re willing to wait for some of it to complete. (We tell you which examples take a long time to run.)
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Deep
Learning
by John Paul Mueller
and Luca Massaron
Deep Learning For Dummies
®
Published by: John Wiley & Sons, Inc., 111 River Street, Hoboken, NJ 07030-5774, www.wiley.com
Copyright © 2019 by John Wiley & Sons, Inc., Hoboken, New Jersey
Media and software compilation copyright © 2019 by John Wiley & Sons, Inc. All rights reserved.
Published simultaneously in Canada
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Library of Congress Control Number is available from the publisher: 2019937505
ISBN 978-1-119-54304-6 (pbk); ISBN 978-1-119-54303-9 (ebk); ISBN ePDF 978-1-119-54302-2 (ebk)
Manufactured in the United States of America
10 9 8 7 6 5 4 3 2 1
Contents at a Glance
Introduction ........................................................1
Part 1: Discovering Deep Learning ..............................7
CHAPTER 1: Introducing Deep Learning .......................................9
CHAPTER 2: Introducing the Machine Learning Principles ......................25
CHAPTER 3: Getting and Using Python .......................................45
CHAPTER 4: Leveraging a Deep Learning Framework ..........................73
Part 2: Considering Deep Learning Basics ....................91
CHAPTER 5: Reviewing Matrix Math and Optimization .........................93
CHAPTER 6: Laying Linear Regression Foundations ...........................111
CHAPTER 7: Introducing Neural Networks ...................................131
CHAPTER 8: Building a Basic Neural Network ................................149
CHAPTER 9: Moving to Deep Learning ......................................163
CHAPTER 10: Explaining Convolutional Neural Networks .......................179
CHAPTER 11: Introducing Recurrent Neural Networks .........................201
Part 3: Interacting with Deep Learning ......................215
CHAPTER 12:PerformingImageClassication ................................217
CHAPTER 13: Learning Advanced CNNs ......................................233
CHAPTER 14: Working on Language Processing ...............................251
CHAPTER 15:GeneratingMusicandVisualArt ................................269
CHAPTER 16: Building Generative Adversarial Networks ........................279
CHAPTER 17: Playing with Deep Reinforcement Learning .......................293
Part 4: The Part of Tens .........................................307
CHAPTER 18: Ten Applications that Require Deep Learning .....................309
CHAPTER 19: Ten Must-Have Deep Learning Tools ............................317
CHAPTER 20: Ten Types of Occupations that Use Deep Learning ................327
Index ...............................................................335
Deep Learning
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