R, TERR, Spark and Python are tools that benefit from larger systems. Software-Defined Servers enable data scientists to size their processing system to the size of a particular data problem. In this Data Science Central webinar you will learn how Software-Defined Servers work in practice for several common data science tools and will explore how removing core and memory constraints has multiple, profound and positive implications for application developers tackling big data problems of all kinds.
Speaker: Michael Berman, Vice President of Engineering — TidalScale
Hosted by: Bill Vorhies, Editorial Director — Data Science Central