Mahout in Action

Sean Owen, Robin Anil, Ted Dunning, Ellen Friedman (Autoren)

Buch | Softcover

375 Seiten

2011
Manning Publications (Verlag)
978-1-935182-68-9 (ISBN)

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HIGHLIGHT

The first and only book on Apache Mahout, an open source tool for

leveraging machine learning techniques in large-scale applications.

DESCRIPTION

To benefit from prior experience in the use of a website, machine

learning techniques are increasingly used. The Apache Mahout project

is focused on three types of machine learning that are of particular

interest to modern web developers—recommendation systems,

classification, and clustering.

Through real-world examples, Mahout in Action introduces the sorts of

problems that these techniques are appropriate for, and then illustrates

how Mahout can be applied to solve them. It places particular focus on

issues of scalability, and how to apply these techniques at very large

scale with the Apache Hadoop framework.

KEY POINTS

This book assumes familiarity with Java, and some basic grounding in

machine learning techniques.

F • First and only book devoted to Apache Mahout

F • Practical insights from industry practitioners

F • Real-world examples

F • Discussion of large-scale implemetation with Hadoop

Sean Owen has been a practicing software engineer for 9 years, most recently at Google, where he helped build and launch Mobile Web search. He joined Apache's Mahout machine learning project in 2008 as a primary committer and works as a Mahout consultant. Robin Anil is a committer at Mahout and works as a full-time Software Engineer at Google.

Erscheint lt. Verlag	12.10.2011
Verlagsort	New York
Sprache	englisch
Maße	231 x 189 mm
Gewicht	704 g
Themenwelt	Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
	Informatik ► Theorie / Studium ► Algorithmen
	Mathematik / Informatik ► Informatik ► Web / Internet
ISBN-10	1-935182-68-4 / 1935182684
ISBN-13	978-1-935182-68-9 / 9781935182689
Zustand	Neuware