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2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Very good book on Apache Mahout
This book provides very good description of large scale machine learning with Apache Mahout. Although it doesn't cover theoretical foundations of machine learning algorithms, it provides very good coverage of main features and algorithms implemented in Mahout - making recommendations, data clustering & classification (although more features are implemented in...
Veröffentlicht am 17. Oktober 2011 von Alexey Ott

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3 von 3 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen Good to get going with Mahout
This book really helps to get started with Apache Mahout - but for me it seemed that in some parts the book really misses some structure. The book is separated into three parts (Recommender systems, clustering, classification) and each of them is obviously written by different authors with very different experiences in writing and with different ideas on breadth and depth...
Vor 23 Monaten von T. Nietsch veröffentlicht


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3 von 3 Kunden fanden die folgende Rezension hilfreich
3.0 von 5 Sternen Good to get going with Mahout, 19. August 2012
Rezension bezieht sich auf: Mahout in Action (Taschenbuch)
This book really helps to get started with Apache Mahout - but for me it seemed that in some parts the book really misses some structure. The book is separated into three parts (Recommender systems, clustering, classification) and each of them is obviously written by different authors with very different experiences in writing and with different ideas on breadth and depth for their topics. E.g. the recommender systems explains how to get the recommender going as a webservice but misses some depth when it comes to details of the algorithm implementations. The other two parts on the other hand mainly rely on the commandline and don't their explanation on how to get things into production didn't really convince me.

Due to the split into three parts and due to the missing structure, some topics keep repeating in each of these three parts (eg. distance metrics explainations) and waste too much space (and reading time), some important aspects are explained in (well hidden) 4th level sections while others (imho) less important aspects got much more attention in own main sections.

What I missed throughout the entire book was an explanation how to write (useful) unittests for the newly developed code - although Mahout and the Mahout Examples ship some good stuff within their sourcecode, I really can't think of a reason why it made sense to leave that out of the book.

Nevertheless if you're going to look at Mahout this book is still worth it's money, mainly because of the time savings you'll have and because it enables you to play around with all the algorithms within the library to earn some experience.
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5.0 von 5 Sternen Very good book on Apache Mahout, 17. Oktober 2011
Rezension bezieht sich auf: Mahout in Action (Taschenbuch)
This book provides very good description of large scale machine learning with Apache Mahout. Although it doesn't cover theoretical foundations of machine learning algorithms, it provides very good coverage of main features and algorithms implemented in Mahout - making recommendations, data clustering & classification (although more features are implemented in Mahout).

Book contains many examples (written against latest released version, 0.5), that could be very useful during read, and they could be reused in your own projects. So, if you're interested in machine learning on big data, then this book is highly recommended
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5.0 von 5 Sternen A must read ..., 19. Februar 2014
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Rezension bezieht sich auf: Mahout in Action (Taschenbuch)
... for all who want to jump on the big-data band wagen.
Mahout abstracts math complexity away from dev work, and this book makes Mahout look easy.
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Mahout in Action von Ellen Friedman (Taschenbuch - 12. Oktober 2011)
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