Jerome Nilmeier

Data Scientist / Data Engineer (IBM)
Jerome Nilmeier is a Data Scientist/Developer at the Spark Technology Center and Cognitive Open AI Group. His duties include Apache Spark development, teaching, and community outreach, and support for all things Spark within IBM, including working with client engagement and enablement dealing with deep engineering and code migration issues, along with machine learning algorithm implementations. He has a BS in Chemical Engineering from UC Berkeley and a PhD in Computational Biophysics from UC San Francisco, and has carried out postdoctoral research in biophysics and bioinformatics at UC Berkeley, Lawrence Berkeley and Livermore Laboratories, and Stanford. He completed the Insight Data Engineering program in late 2014, just before joining IBM.

Getting Started with Machine Learning on Apache Spark

Join us for a basic introduction to Apache Spark with Jerome Nilmeier, Data Scientist and Apache Spark expert, to learn how to get started with Machine Learning using Scala and Apache Spark. After this training you will be able to write and run a sample Scala application using Apache Spark. Attendees will learn: Fundamentals of Scala. Why Scala is best for leveraging Apache Spark (we will also review other languages: Python, R)Fundamentals of Apache SparkCoding examples from all of the main libraries of Apache Spark (SparkSQL, MLlib, GraphX, Spark Streaming, and SparkR), with particular emphasis on the machine learning libraries, including open source projects that run on the Spark framework (SystemML, R4ML).
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