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Wednesday, May 11 • 10:50am - 11:40am
SystemML - Declarative Machine Learning - Luciano Resende, IBM

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Machine learning in the enterprise is an iterative process. Data scientists will tweak or replace their learning algorithm in a small data sample until they find an approach that works for the business problem and then apply the Analytics to the full data set. Apache SystemML is a new system that accelerates this kind of exploratory algorithm development for large-scale machine learning problems. SystemML provides a high-level language to quickly implement and run machine learning algorithms on Spark. SystemML’s cost-based optimizer takes care of low-level decisions about how to use Spark’s parallelism, allowing users to focus on the algorithm and the real-world problem that the algorithm is trying to solve. This talk will introduce you to SystemML and get you started building declarative analytics with SystemML using a simple Zeppelin notebook and running on Apache Spark environment.

Speakers
avatar for Luciano Resende

Luciano Resende

Architect, Spark Technology Center, IBM
Luciano Resende is an Architect in IBM Analytics. He has been contributing to open source at The ASF for over 10 years, he is a member of ASF and is currently contributing to various big data related Apache projects including Spark, Zeppelin, Bahir. Luciano is the project chair for Apache Bahir, and also spend time mentoring newly created Apache Incubator projects. At IBM, he contributed to several IBM big data offerings, including BigInsights... Read More →


Wednesday May 11, 2016 10:50am - 11:40am
Georgia A

Attendees (34)