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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.
Ted Dunning is Chief Application Architect at MapR Technologies and committer and PMC member for the Apache Mahout project. He contributing to the Mahout clustering, classification and matrix decomposition algorithms. He was the chief architect behind the MusicMatch (now Yahoo Music) and Veoh recommendation systems, and built fraud detection systems for ID Analytics.
Ellen Friedman is an experienced writer with a doctorate in biochemistry. In addition to a research career, she has written on a wide range of scientific and technical topics including molecular biology, medicine and earth science.
I purchased this book while preparing for a Mahout recommender system implementation for a customer, read it a little bit, and then set it down to start work. Read morePublished 12 months ago by Andrew
I found this book and the included examples to be an excellent starting point to gain exposure to the various facets of machine learning. Read morePublished 22 months ago by java coder
I found this book to be a very helpful guide. It has a number of useful examples, and the explanations are clearly written. Read morePublished on May 22, 2013 by Robert L McPherson
Mahout in Action (MiA) offers a nice introduction to Mahout and machine learning. MiA progresses at a good pace and provides nice background on Mahout's core abilities: recommender... Read morePublished on January 29, 2013 by Ricardo A. Radaelli-Sanchez
I bought this book online here, so that I can get the ebook and also the paperback copy of the book. Read morePublished on August 17, 2012 by Sandeep
This book is way TOO verbose. I think at least 2/3 of the contents can be cut without affecting anything, which is in fact the general feeling I have for all "*** in action" series... Read morePublished on May 5, 2012 by Runpu Sun
This book has been very helpful implementing multiple machine learning algorithms. The examples are very good and do a great job helping me to understand the software.Published on April 23, 2012 by Jonathan Maurer
This is a very well written book, good examples & very good for beginners. I would request the authors to keep revising the book as mahout upgrades to newer versions. Read morePublished on March 10, 2012 by Cyril A. Furtado