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Hadoop and Machine Learning

The Big Data buzzword represents the convergence of massive, dynamic data sets with powerful techniques for effective use of that data.  At the core is a scale-out architecture involving distributed computation and storage. 

Machine learning algorithms are adapting to work effectively in distributed environments. Eron will examine a few frameworks and tools for scale-out machine learning algorithms.  We will discuss how the Hadoop framework is evolving to support a greater diversity of machine learning algorithms.  We will touch on the use of the cloud for hosting scale-out machine learning projects. 

The session will consist of a presentation, some demonstrations, and open discussion.

About the speaker:

Eron Wright is a Director of Engineering at EMC.   Eron works on the ViPR product, delivering data services for petabyte-scale storage with integrated Hadoop capabilities.  Eron was formerly a developer at Microsoft, working on the Windows Azure platform.  In his spare time, he is a machine learning hobbyist, and welcomes our new sentient overlords!

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