commit | aab2e08f73171b8abef363b22107ab6c2f90aedf | [log] [tgz] |
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author | arnabp <arnab.phani@tugraz.at> | Mon Oct 05 16:37:44 2020 +0200 |
committer | arnabp <arnab.phani@tugraz.at> | Mon Oct 05 16:39:33 2020 +0200 |
tree | b18d39c0e5b1d81caa343a891ccfef2b1bc0d5c1 | |
parent | 18628f07cd027b8dd9938b5f23fee7183e8357e7 [diff] |
[SYSTEMDS-2667] Fix extra/NOTICE
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.
Quick Start Install, Quick Start and Hello World
Documentation: SystemDS Documentation
Python Documentation Python SystemDS Documentation
Issue Tracker Jira 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