Introducing R4ML - A New Open Source R Package for Scalable Machine Learning!

May 25, 2017 · Sunnyvale, United States of America

R is the de facto standard for statistics and analysis. In this talk, we introduce R4ML, a new open-source R package for scalable machine learning from IBM. R4ML provides a bridge between R, Apache SystemML and SparkR, allowing R scripts to invoke custom algorithms developed in SystemML's R-like domain specific language. This capability also provides a bridge to the algorithm scripts that ship with Apache SystemML, effectively adding a new library of prebuilt scalable algorithms for R on Apache Spark.  R4ML integrates seamlessly SparkR, so data scientists can use the best features of SparkR and SystemML together in the same script. In addition, the R4ML  package provides a number of useful new scalable R functions that simplify common data cleaning and statistical analysis tasks.

This talk will begin with an overview of the R4ML package, its API, supported canned algorithms, and the integration to Spark and SystemML. We will walk through a small example of creating a custom algorithm and a demo of a canned algorithm. We will share our experiences using R4ML technology with IBM clients. The talk will conclude with pointers to how the audience can try out R4ML and discuss potential areas of community collaboration.

Speakers:
Alok Singh is a Principal Engineer at the IBM Spark Technology Center, where he leads the R4ML project. He has built and architected multiple analytical frameworks and implemented various machine learning algorithms. His interest is in creating Big Data and scalable machine learning software and algorithms.

Fred Reiss is Chief Architect at the IBM Spark Technology Center in San Francisco and is one of the founding employees of the Center. Fred received his Ph.D. from UC Berkeley in 2006, then worked for IBM Research Almaden for the next nine years. At Almaden, Fred worked on the SystemML and SystemT projects, as well as on the research prototype of DB2 with BLU Acceleration. Fred has over 25 peer-reviewed publications and six patents.

Drinks and light appetizers will be served.


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