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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.

Owners of a Manning pBook purchased anywhere in the world can download a free eBook from manning.com at any time. They can do so multiple times and in any or all formats available (PDF, ePub or Kindle). To do so, customers must register their printed copy on Manning's site by creating a user account and then following instructions printed on the pBook registration insert at the front of the book.

 

what's Inside
Use data group 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
Meet Apache Mahout
PART 1 RECOMMENDATIONS
Introducing recommenders
Representing recommender data
Making recommendations
Taking recommenders production to
Distributing recommendation computations
PART 2 CLUSTERING
Introduction to clustering
Representing data
Clustering algorithms in Mahout
Evaluating and improving clustering quality
Taking clustering production to
Real-world applications of clustering
PART 3 CLASSIFICATION
Introduction to classification
Training a класифікатор
Evaluating and tuning a класифікатор
Deploying a класифікатор
Case study: Shop It To Me

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Mahout in Action

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