| commit | e3ec921e0d8ed9f883fc534c18f28bdb79b315fa | [log] [tgz] |
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| author | dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> | Sun Jan 21 14:20:05 2024 +0000 |
| committer | GitHub <noreply@github.com> | Sun Jan 21 14:20:05 2024 +0000 |
| tree | 64f36fa71d02b9af9932e806a271b97cdca6a3c0 | |
| parent | ceb50a2d2175390267796e0cfd8620ca251c1e3d [diff] |
Bump org.apache.derby:derby from 10.14.2.0 to 10.17.1.0 Bumps org.apache.derby:derby from 10.14.2.0 to 10.17.1.0. --- updated-dependencies: - dependency-name: org.apache.derby:derby dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com>
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 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
