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Hands-on-Machine-Learning-with-Scikit-learn, Keras & Tensorflow英文书
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Aurélien Géron
Hands-on Machine Learning with
Scikit-Learn, Keras, and
TensorFlow
Concepts, Tools, and Techniques to
Build Intelligent Systems
SECOND EDITION
Boston Farnham Sebastopol
Tokyo
Beijing Boston Farnham Sebastopol
Tokyo
Beijing
978-1-492-03264-9
[LSI]
Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow
by Aurélien Géron
Copyright © 2019 Aurélien Géron. All rights reserved.
Printed in the United States of America.
Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472.
O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are
also available for most titles (http://oreilly.com). For more information, contact our corporate/institutional
sales department: 800-998-9938 or corporate@oreilly.com.
Editor: Nicole Tache
Interior Designer: David Futato
Cover Designer: Karen Montgomery
Illustrator: Rebecca Demarest
June 2019: Second Edition
Revision History for the Early Release
2018-11-05: First Release
2019-01-24: Second Release
2019-03-07: Third Release
2019-03-29: Fourth Release
2019-04-22: Fifth Release
See http://oreilly.com/catalog/errata.csp?isbn=9781492032649 for release details.
The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Hands-on Machine Learning with
Scikit-Learn, Keras, and TensorFlow, the cover image, and related trade dress are trademarks of O’Reilly
Media, Inc.
While the publisher and the author have used good faith efforts to ensure that the information and
instructions contained in this work are accurate, the publisher and the author disclaim all responsibility
for errors or omissions, including without limitation responsibility for damages resulting from the use of
or reliance on this work. Use of the information and instructions contained in this work is at your own
risk. If any code samples or other technology this work contains or describes is subject to open source
licenses or the intellectual property rights of others, it is your responsibility to ensure that your use
thereof complies with such licenses and/or rights.
Table of Contents
Preface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
Part I. The Fundamentals of Machine Learning
1.
The Machine Learning Landscape. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
What Is Machine Learning? 4
Why Use Machine Learning? 4
Types of Machine Learning Systems 8
Supervised/Unsupervised Learning 8
Batch and Online Learning 15
Instance-Based Versus Model-Based Learning 18
Main Challenges of Machine Learning 24
Insufficient Quantity of Training Data 24
Nonrepresentative Training Data 26
Poor-Quality Data 27
Irrelevant Features 27
Overfitting the Training Data 28
Underfitting the Training Data 30
Stepping Back 30
Testing and Validating 31
Hyperparameter Tuning and Model Selection 32
Data Mismatch 33
Exercises 34
2.
End-to-End Machine Learning Project. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
Working with Real Data 38
Look at the Big Picture 39
iii
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