Master Big Data at Hadoop Day

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REGISTER  |  PROGRAM  |  VENUE  |  DATA SUMMIT FEATURED EVENT AT H103: Harnessing Big Data With Spark Apache Spark, an engine for large-scale data processing, can be complementary to Hadoop but it can also be deployed without it. Find out what Spark offers and why it is gaining ground in the world of Big Data. The introduction of Hadoop MapReduce (MR) allowed the application of algorithms to data of unprecedented scale using systems built from cheap commodity hardware. However, MR is slow, significantly curtailing its applicability to advanced iterative machine learning (ML) algorithms. These algorithms frequently need to be run multiple times in order to effectively train and optimally parameterize. Spark changed this, and, by providing speedups of 100X or more, fundamentally introduced the possibility of applying ML to Big Data and extracting meaningful insights in actionable timeframes. This presentation provides an overview of the framework Alpine Data developed and present results for a variety of well-known datasets, illustrating how the software can significantly eliminate the repetitive, trial-and-error nature of today's data science and reduce the time to an effective model. Apache Spark and Effective Machine Learning Tuesday, May 10, 2016 | 2:00 p.m. - 2:45 p.m. Lawrence Spracklen VP, Engineering, Alpine Data Whether your organization is currently considering Hadoop or already using it in production, Hadoop Day is your opportunity to connect with the experts in New York City and advance your knowledge base. This unique educational event has all the bases covered! Join us and learn more about the best practices from real-world practitioners.   Register with a Gold Pass to include Hadoop Day and save an EXTRA $100! DIAMOND SPONSORS PLATINUM SPONSORS GOLD SPONSOR MEDIA SPONSORS

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