commit | e929457e2f1850e6f1c2b5c490523f9526e51be5 | [log] [tgz] |
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author | Sven Celin <sven.celin@gmail.com> | Sat Oct 10 19:38:10 2020 +0200 |
committer | Matthias Boehm <mboehm7@gmail.com> | Sat Oct 10 19:38:10 2020 +0200 |
tree | 925429343d0001fb8a782d175e5a1e751774f98b | |
parent | f2f6dbdab9fd451cfe64093b1f3b8738c314fce7 [diff] |
[SYSTEMDS-2682/3] New Lasso and PPCA built-in functions AMLS project SS2020. Closes #1071.
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