commit | 58ec5030ecbc24c27a771ef9535f1697c1d60fa6 | [log] [tgz] |
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author | Milan Kacar <milankacar@live.com> | Wed Feb 24 22:08:39 2021 +0100 |
committer | baunsgaard <baunsgaard@tugraz.at> | Mon Mar 01 11:35:42 2021 +0100 |
tree | e6d2be8289d317bdf84f393fb0c33604a5df1ec3 | |
parent | 68e5e298c73d1013c528d76c789dba77fd106eb8 [diff] |
[SYSTEMDS-2842] Cspline Builtin DIA project WS2020/21 This commit add cspline to the builtin functions Co-authored-by: aleksapand <pandurevic@student.tugraz.at> Co-authored-by: Stefan Gajanovic <stefan.gajanovic@me.com>
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