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Wednesday, May 11 • 4:10pm - 5:00pm
Distributed Machine Learning with Apache Mahout - Suneel Marthi, Red Hat

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Data Science tools like R,Scikit-Learn as they offer a convenient and familiar syntax for analysis tasks. However, these systems are limited to operating serially on data sets that can fit on a single node. Mahout-Samsara is a linear algebra environment that offers both an easy-to-use Scala DSL and efficient distributed execution for linear algebra operations.In this talk, we will look at Mahout’s distributed linear algebra capabilities and build a simple ML algorithm using the Samsara DSL. We’ll be demonstrating this using Apache Flink as the backend distributed engines.ML practitioners will come away from this talk with a better understanding of how Samsara’s linear algebra environment can help simplify developing highly scalable ML algorithms by focusing solely on the declarative specification of the algorithm while not worrying about the details of scalable distributed implementation

avatar for Suneel Marthi

Suneel Marthi

Suneel is a Member of Apache Software Foundation and is a Committer and PMC on Apache Mahout, Apache OpenNLP, Apache Streams. He's presented in the past at Flink Forward, Hadoop Summit, Berlin Buzzwords, Machine Learning Conference, Big Data Tech Warsaw and Apache Big Data.

Wednesday May 11, 2016 4:10pm - 5:00pm PDT
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