for questions about SystemML's declarative large-scale machine learning
Apache SystemML is a framework for large scale machine learning. Algorithms are specified using the Declarative Machine Learning (DML) language, which has an R-like syntax and built-in support for linear algebra, mathematical and I/O operations. DML is compiled and optimized into a program for distributed execution over Spark or Hadoop.
SystemML uses database compression techniques to allow in-memory computation over large datasets that would otherwise require streaming computation.
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