Practical Machine Learning: Innovations in Recommendation

Name: Practical Machine Learning: Innovations in Recommendation
Price: 17.83 USD
Availability: InStock
ISBN: 9781491915387

ISBN-10: 1491915382

ISBN-13: 9781491915387

Edition: 2014

Authors: Ted Dunning, Ellen Friedman

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Description:

Building a simple but powerful recommendation system is much easier than you think. Approachable for all levels of expertise, this report explains innovations that make machine learning practical for business production settings—and demonstrates how even a small-scale development team can design an effective large-scale recommendation system.Apache Mahout committers Ted Dunning and Ellen Friedman walk you through a design that relies on careful simplification. You’ll learn how to collect the right data, analyze it with an algorithm from the Mahout library, and then easily deploy the recommender using search technology, such as Apache Solr or Elasticsearch. Powerful and effective, this…

Book details

Copyright year: 2014
Publisher: O'Reilly Media, Incorporated
Publication date: 3/18/2016
Binding: Paperback
Pages: 56
Size: 6.34" wide x 8.94" long x 0.17" tall
Weight: 0.220
Language: English

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 joined Apache's Mahout project as a Google Summer of Code student in 2008 and contributed to the Classifier and Frequent Pattern Mining packages with algorithms that run on the Hadoop Map/Reduce platform. Since 2009, he has been a committer at Mahout and works as a full-time Software Engineer at Google.