commit | 8d1dfe92499e3138d2397423930865e64d77e91c | [log] [tgz] |
---|---|---|
author | Janardhan Pulivarthi <j143@protonmail.com> | Tue Sep 29 09:30:04 2020 +0530 |
committer | baunsgaard <baunsgaard@tugraz.at> | Wed Sep 30 17:24:04 2020 +0200 |
tree | 72b5bb183eebaf6d25c498edfc747c30a07bb942 | |
parent | da79944a1581ea079dc77758e507de99a2863226 [diff] |
[MINOR][DOC] Update header links and image files Fix relative path when inside site closes #1072
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