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Mahout in Action


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.

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

Table of Contents

  1. Meet Apache Mahout

PART 1 RECOMMENDATIONS

  1. Introducing recommenders
  2. Representing recommender data
  3. Making recommendations
  4. Taking recommenders to production
  5. Distributing recommendation computations

PART 2 CLUSTERING

  1. Introduction to clustering
  2. Representing data
  3. Clustering algorithms in Mahout
  4. Evaluating and improving clustering quality
  5. Taking clustering to production
  6. Real-world applications of clustering

PART 3 CLASSIFICATION

  1. Introduction to classification
  2. Training a classifier
  3. Evaluating and tuning a classifier
  4. Deploying a classifier

Book Details

  • Paperback: 416 pages
  • Publisher: Manning Publications (October 2011)
  • Language: English
  • ISBN-10: 1935182684
  • ISBN-13: 978-1935182689
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