Difference between revisions of "Mahout"
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* ''[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]] | * ''[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: Java]] | ||
[[Category: Software]] | [[Category: Software]] | ||
Revision as of 10:51, 9 February 2012
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.
