Past Meetup

Special Event- Scaling R Using Parallel External Memory Algorithms

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Have you ever wanted to scale R but are limited due to memory? In this talk Joseph Rickert, blogger, data scientist and R community Ambassador introduces the latest R technology to scale your data analysis.


Microsoft R Server (formerly Revolution R Enterprise) has become the foundation for Microsoft’s use or the R language to tackle big-data machine learning and predictive analytics tasks. At the heart of MRS is the RevoScaleR package that implements a number of parallel external memory algorithms. These “PEMAs” are inherently parallel and designed for distributed computing on large data sets. Unlike standard open source R functions they do not require all of the data to be in memory at one time. I will provide an overview of MRS and show some examples of PEMAs working on data sets too large to be processed by open source R algorithms on my laptop.


Joseph Rickert is a Program Manager and R Community Ambassador for Microsoft. He came to Microsoft with the rest of Revolution Analytics team where he worked as a data scientist, blog editor and special programs manager. He is currently Microsoft’s representative to the R Consortium’s Infrastructure Steering Committee and a member of the organizing committee for useR!2016.

Previously, Joe held a variety of technical and marketing roles while working for technology startups that spanned multiple industries from local area networks to disk drives, test equipment and health care. Joe entered Franklin & Marshall college on a Classics scholarship and end up a Math major. He also earned an M.A. in Humanities and an M.S. in Statistics from the California State University. You can follow Joe on Twitter as @RevoJoe


6:30-6:50 - Networking
6:50-7:00 - Introductions
7:00 - 7:50 - Talk
7:50 - 8:30 - Socializing

-- NOTE --

This event has limited seating capacity.

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*The event is FREE to attend but reserving your place through Eventbrite guarantee's your place.


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