Skip to content

An open source ML system for the end-to-end data science lifecycle

License

Notifications You must be signed in to change notification settings

corepointer/systemds_tug

 
 

Repository files navigation

SystemDS

Overview: SystemDS is a versatile system for the end-to-end data science lifecycle from data integration, cleaning, and feature engineering, over efficient, local and distributed ML model training, to deployment and serving. To this end, we aim to provide a stack of declarative languages with R-like syntax for (1) the different tasks of the data-science lifecycle, and (2) users with different expertise. These high-level scripts are compiled into hybrid execution plans of local, in-memory CPU and GPU operations, as well as distributed operations on Apache Spark. In contrast to existing systems - that either provide homogeneous tensors or 2D Datasets - and in order to serve the entire data science lifecycle, the underlying data model are DataTensors, i.e., tensors (multi-dimensional arrays) whose first dimension may have a heterogeneous and nested schema.

Documentation: SystemDS Documentation

Status and Build: SystemDS is still in pre-alpha status. The original code base was forked from Apache SystemML 1.2 in September 2018. We will continue to support linear algebra programs over matrices, while replacing the underlying data model and compiler, as well as substantially extending the supported functionalities. Until the first release, you can build your own snapshot via Apache Maven: mvn -DskipTests clean package.

Status

Build Status License

Build Documentation Component Test Application Test Function Test Python Test

About

An open source ML system for the end-to-end data science lifecycle

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Java 90.3%
  • R 6.2%
  • Shell 1.2%
  • Python 0.8%
  • Cuda 0.7%
  • C++ 0.3%
  • Other 0.5%