SystemML Documentation

SystemML is a flexible, scalable machine learning system. SystemML’s distinguishing characteristics are:

  1. Algorithm customizability via R-like and Python-like languages.
  2. Multiple execution modes, including Spark MLContext, Spark Batch, Hadoop Batch, Standalone, and JMLC.
  3. Automatic optimization based on data and cluster characteristics to ensure both efficiency and scalability.

The SystemML GitHub README describes building, testing, and running SystemML. Please read Contributing to SystemML to find out how to help make SystemML even better!

To download SystemML, visit the downloads page.

This version of SystemML supports: Java 8+, Scala 2.11+, Python 2.7/3.5+, Hadoop 2.6+, and Spark 2.1+.

Running SystemML

Language Guides

ML Algorithms