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Mahout in Action

3.73  ·  Rating details ·  90 ratings  ·  5 reviews

When computers harness prior experience to improve future performance, a type of artificial intelligence called machine learning has been applied. The Apache Mahout project is focused on three types of machine learning that are of particular interest to modern web developers "recommendation systems, classification, and clustering.



Through real-world examples, Mahout in Ac

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Paperback, 415 pages
Published October 14th 2011 by Manning Publications (first published October 5th 2011)
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Alex Ott
Feb 15, 2011 rated it it was amazing
This book doesn't provide deep coverage of theoretical foundations of machine learning (I would recommend to look to other books, like "Introduction to Machine Learning (Adaptive Computation and Machine Learning series)", "Machine Learning in Action" or "Programming Collective Intelligence: Building Smart Web 2.0 Applications", etc., if you want to get more background), but concentrates on explanation on how to use Apache Mahout to solve some of machine learning problems: making recommendations, ...more
Jaganadh Gopinadhan
Mar 02, 2011 rated it it was amazing
Apache Mahout is an Open Source scalable Machine Learning library in Java. It is designed to handle large data set. More than a dozen of Machine Learning and Data Mining algorithms are available in Mahout. All those algorithms are implemented on top of Apache Hadoop. The framework is distributed under a commercially friendly Apache License. It helps researchers and corporate to build scalable and practical products based on Machine Learning and Data Mining Principles. A wide range of big compani ...more
Todd N
Nov 23, 2012 rated it really liked it
Shelves: big-data
Read this very quickly in preparation for a meeting. Because the Apache Mahout documentation is bad, even by open source standards, this is the best source for learning Mahout. It contains a very good overview of item-based and user-based recommendation engines if you have ever wondered how these things work. Classification and clustering are also covered nicely.

Obviously the software has continued to be developed since this book was published, so it is dated. There are a section explaining how
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Andrey Tatarinov
Jan 04, 2013 rated it liked it
Very long and not very informative Mahout quickstart. Could be just as easily be in form of a wiki article with JavaDoc's references.
Daniel Korzekwa
May 05, 2011 rated it liked it
Reading this book helps to get up to speed with Apache Mahout project, especially that at the moment online documentation for Apache Mahout is quite poor and incomplete.
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