Apache Mahout – Overview

Mahout’s goal is to build scalable machine learning libraries. With scalable we mean:

* Scalable to reasonably large data sets. Our core algorithms for clustering, classfication and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. However we do not restrict contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for non-distributed algorithms.
* Scalable to support your business case. Mahout is distributed under a commercially friendly Apache Software license.
(Link: Apache Mahout – Overview)