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Apache Spark: Distributed Machine Learning using MLbase

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Published on Aug 16, 2013

Ameet Talwalker and Evan Sparks present their work on the MLbase project which will be a distributed Machine Learning platform on top of Apache Spark. This presentation was given at Twitter on August 6th 2013. http://mlbase.org/

http://www.meetup.com/spark-users/eve...
In this talk we describe our efforts, as part of the MLbase project, to develop a distributed Machine Learning platform on top of Spark. In particular, we present the details of two core components of MLbase, namely MLlib and MLI, which are scheduled for open-source release this summer. MLlib provides a standard Spark library of scalable algorithms for common learning settings such as classification, regression, collaborative filtering and clustering. MLI is a machine learning API that facilitates the development of new ML algorithms and feature extraction methods. As part of our release, we include a library written against the MLI containing standard and experimental ML algorithms, optimization primitives and feature extraction methods.

http://spark-project.org/
http://incubator.apache.org/projects/...

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