Difference between revisions of "Mahout"
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Mahout is written in Java, parts of it are written using the MapReduce programming paradigm in order to enable large scale distribution of algorithmic computation using [http://hadoop.apache.org Apache Hadoop]. | Mahout is written in Java, parts of it are written using the MapReduce programming paradigm in order to enable large scale distribution of algorithmic computation using [http://hadoop.apache.org Apache Hadoop]. | ||
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| + | == Literature == | ||
| + | * Sean Owen, Robin Anil, Ted Dunning, Ellen Friedman: ''[http://www.manning.com/owen/ Mahout in Action]'', Manning, 2011. | ||
== External links == | == External links == | ||
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* [http://code.google.com/p/unresyst/wiki/CreateMahoutRecommender Mahout for Newbies: How to Create a Recommender] | * [http://code.google.com/p/unresyst/wiki/CreateMahoutRecommender Mahout for Newbies: How to Create a Recommender] | ||
* [[Wikipedia: Apache Mahout]] | * [[Wikipedia: Apache Mahout]] | ||
| + | * ''[http://ssc.io/deploying-a-massively-scalable-recommender-system-with-apache-mahout/ Deploying a massively scalable recommender system with Apache Mahout]'', blog post by [[Sebastian Schelter]] | ||
| − | [[Category:Software]] | + | [[Category: Software]] |
Revision as of 05:35, 10 November 2011
Apache Mahout is a scalable machine learning library that supports large data sets. Mahout also contains implementations of several collaborative filtering algorithms.
Mahout is written in Java, parts of it are written using the MapReduce programming paradigm in order to enable large scale distribution of algorithmic computation using Apache Hadoop.
Literature
- Sean Owen, Robin Anil, Ted Dunning, Ellen Friedman: Mahout in Action, Manning, 2011.
