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You're reading from  Apache Mahout Essentials

Product typeBook
Published inJun 2015
Reading LevelIntermediate
Publisher
ISBN-139781783554997
Edition1st Edition
Languages
Java
Tools
Mahout
Concepts
Machine Learning
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Author (1)
Jayani Withanawasam
Jayani Withanawasam
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Jayani Withanawasam

Jayani Withanawasam is R&D engineer and a senior software engineer at Zaizi Asia, where she focuses on applying machine learning techniques to provide smart content management solutions. She is currently pursuing an MSc degree in artificial intelligence at the University of Moratuwa, Sri Lanka, and has completed her BE in software engineering (with first class honors) from the University of Westminster, UK. She has more than 6 years of industry experience, and she has worked in areas such as machine learning, natural language processing, and semantic web technologies during her tenure. She is passionate about working with semantic technologies and big data.
Read more about Jayani Withanawasam

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Summary

The Apache Mahout recommendations module helps you to recommend items to users which they have not seen before, based on their previous preferences. The collaborative filtering approach is implemented in Mahout. User-based recommendations, item-based recommendations, and matrix factorization are the key approaches that are geared toward collaborative filtering in Mahout.

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Apache Mahout Essentials
Published in: Jun 2015Publisher: ISBN-13: 9781783554997
© 2015 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Jayani Withanawasam

Jayani Withanawasam is R&D engineer and a senior software engineer at Zaizi Asia, where she focuses on applying machine learning techniques to provide smart content management solutions. She is currently pursuing an MSc degree in artificial intelligence at the University of Moratuwa, Sri Lanka, and has completed her BE in software engineering (with first class honors) from the University of Westminster, UK. She has more than 6 years of industry experience, and she has worked in areas such as machine learning, natural language processing, and semantic web technologies during her tenure. She is passionate about working with semantic technologies and big data.
Read more about Jayani Withanawasam

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