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Practical Machine Learning with H2O

Machine

learning

Deep

Learning

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Machine learning has finally come of age. With H2O software, you can perform machine learning and data analysis using a simple open source framework that’s easy to use, has a wide range of OS and language support, and scales for big data. This hands-on guide teaches you how to use H20 with only minimal math and theory behind the learning algorithms.

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Darren Cook

Practical Machine

Learning with

H2O

POWERFUL, SCALABLE

TECHNIQUES FOR AI

AND DEEP LEARNING

Darren Cook

Practical Machine Learning

with H2O

Powerful, Scalable Techniques

for Deep Learning and AI

Boston Farnham Sebastopol

Tokyo

Beijing Boston Farnham Sebastopol

Tokyo

Beijing

978-1-491-96460-6

[LSI]

Practical Machine Learning with H2O

by Darren Cook

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/safari). For more information, contact our corporate/insti‐

tutional sales department: 800-998-9938 or corporate@oreilly.com.

Editor: Nicole Tache

Production Editor: Colleen Lobner

Copyeditor: Kim Cofer

Proofreader: Charles Roumeliotis

Indexer: WordCo Indexing Services, Inc.

Interior Designer: David Futato

Cover Designer: Karen Montgomery

Illustrator: Rebecca Demarest

December 2016:

First Edition

Revision History for the First Edition

2016-12-01: First Release

2017-01-06: Second Release

See http://oreilly.com/catalog/errata.csp?isbn=9781491964606 for release details.

The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Practical Machine Learning with H2O,

the cover image of a crayfish, 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. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix

Installation and Quick-Start. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Preparing to Install 1

Installing R 2

Installing Python 2

Privacy 3

Installing Java 3

Install H2O with R (CRAN) 3

Install H2O with Python (pip) 5

Our First Learning 7

Training and Predictions, with Python 11

Training and Predictions, with R 13

Performance Versus Predictions 15

On Being Unlucky 16

Flow 17

Data 17

Models 20

Predictions 20

Other Things in Flow 22

Summary 23

Data Import, Data Export. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Memory Requirements 25

Preparing the Data 26

Getting Data into H2O 28

Load CSV Files 28

Load Other File Formats 30

iii

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