Apache Mahout Essentials

Implement top-notch machine learning algorithms for classification, clustering, and recommendations with Apache Mahout

By: Jayani Withanawasam

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eText | 19 June 2015 | Edition Number 1

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Book Description

If you are a Java developer or data scientist, haven't worked with Apache Mahout before, and want to get up to speed on implementing machine learning on big data, then this is the perfect guide for you.

What you will learn

Get started with the fundamentals of Big Data, batch, and realtime data processing with an introduction to Mahout and its applications
Understand the key machine learning concepts behind algorithms in Apache Mahout
Apply machine learning algorithms provided by Apache Mahout in realworld practical scenarios
Implement and evaluate widelyused clustering, classification, and recommendation algorithms using Apache Mahout
Discover tips and tricks to improve the accuracy and performance of your results
Set up Apache Mahout in a production environment with Apache Hadoop
Glance at the Spark DSL advancements in Apache Mahout 1.0
Provide dynamic and interactive data visualizations for Apache Mahout
Build a recommendation engine for realtime use cases and use userbased and itembased recommendation algorithms