Mahout in Action:
by Sean Owen, Robin Anil, Ted Dunning, Ellen Friedman

Mahout in Action is a hands-on introduction to machine learning with Apache Mahout. Following real-world examples, the book presents practical use cases and then illustrates how Mahout can be applied to solve them. Includes a free audio- and video-enhanced ebook.

ABOUT THE TECHNOLOGY

A computer system that learns and adapts as it collects data can be really powerful. Mahout, Apache's open source machine learning project, captures the core algorithms of recommendation systems, classification, and clustering in ready-to-use, scalable libraries. With Mahout, you can immediately apply to your own projects the machine learning techniques that drive Amazon, Netflix, and others.

ABOUT THIS BOOK

This book covers machine learning using Apache Mahout. Based on experience with real-world applications, it introduces practical use cases and illustrates how Mahout can be applied to solve them. It places particular focus on issues of scalability and how to apply these techniques against large data sets using the Apache Hadoop framework.

This book is written for developers familiar with Java. No prior experience with Mahout is assumed.

WHAT'S INSIDE

Use group data to make individual recommendations

Find logical clusters within your data

Filter and refine with on-the-fly classification

Free audio and video extras

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Publisher: Manning
Page Count (est.): 387
ISBN10: 1935182684
ISBN13: 9781935182689
Cover: Paperback
Pub Date: 10/13/2011