Mahout in Action by Sean Owen
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.
| SKU | Unavailable |
| ISBN 13 | 9781935182689 |
| ISBN 10 | 1935182684 |
| Title | Mahout in Action |
| Author | Sean Owen |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Manning Publications |
| Year published | 2011-10-12 |
| Number of pages | 375 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |