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Analyzed 4 days ago. based on code collected 4 days ago.

Apache 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

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30 Day Summary

Jul 28 2015 — Aug 27 2015

12 Month Summary

Aug 27 2014 — Aug 27 2015
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