To help our audience leverage the power of machine learning, the editors of insideBIGDATA have created this weekly article series called “The insideBIGDATA Guide to Machine Learning.” This is our eighth and final installment, “Production Deployment Environments for R.”
The debate over which statistical platform sits premiere over the others for data science applications rages on. The discussion often turns to the popular R and SAS environments. But to focus the dialog on performance only, a new benchmark study was just completed by commercial R provider Revolution Analytics.
MapR Technologies, Inc., provider of a leading distribution for Apache Hadoop, today launched at Hadoop Summit the industry’s first Hadoop application gallery. Launching with solutions from a wide range of Hadoop ecosystem partners, the MapR App Gallery is designed to help customers derive greater business value from big data as they scale-out their enterprise data architectures.
As the primary facilitator of data science and big data, machine learning has garnered much interest by a broad range of industries as a way to increase value of enterprise data assets. In this article series we’ll examine the principles underlying machine learning based on the R statistical environment.