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

Clone this repo:
  1. bd17ead [SYSTEMDS-3710] Function entry/exit marker in lineage traces by Arnab Phani · 2 days ago main
  2. 5015f63 [SYSTEMDS-3709] Additional tests for UDF backwards compatibility by Matthias Boehm · 8 days ago
  3. da7889e [SYSTEMDS-3709] Fix backwards compatibility (rowClassMeet UDF) by Matthias Boehm · 9 days ago
  4. 4b3fa93 [SYSTEMDS-3695] Fix spark frame cbind for misaligned inputs by e-strauss · 10 days ago
  5. 0f1c99c [SYSTEMDS-3529] Codecov badge and PyPI downloads badges in README by evelina · 11 days ago

Apache SystemDS

Overview: SystemDS is an open source ML 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.

Quick StartInstall, Quick Start and Hello World
Documentation:SystemDS Documentation
Python DocumentationPython SystemDS Documentation
Issue TrackerJira Dashboard

Status and Build: SystemDS is renamed from SystemML which is an Apache Top Level Project. To build from source visit SystemDS Install from source

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