tag | 56049d23ef1890d405d30a61d956fe028292db29 | |
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tagger | Janardhan Pulivarthi <janardhan@apache.org> | Fri Jun 10 17:55:28 2022 +0000 |
object | 06c7c40350c16b6d96eaf0c34fac07047ec92e5d |
[maven-release-plugin] copy for tag 3.0.0-rc1
commit | 06c7c40350c16b6d96eaf0c34fac07047ec92e5d | [log] [tgz] |
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author | Janardhan Pulivarthi <janardhan@apache.org> | Fri Jun 10 17:55:07 2022 +0000 |
committer | Janardhan Pulivarthi <janardhan@apache.org> | Fri Jun 10 17:55:07 2022 +0000 |
tree | 5c08f2d40cddfc2e8ba7517ceb3b35d1895da63b | |
parent | dd660d53d4ffe53ebd20c8ac23be8dc8f90bfc80 [diff] |
[maven-release-plugin] prepare release 3.0.0-rc1
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