commit | abe4b1d9cecb81c95087f64dd7e572b1ba41abcc | [log] [tgz] |
---|---|---|
author | Artem Kroviakov <mr.krovyak@gmail.com> | Mon Dec 28 19:37:53 2020 +0100 |
committer | arnabp <arnab.phani@tugraz.at> | Mon Dec 28 19:37:53 2020 +0100 |
tree | 158fbcf82dbad4365ff6db20ac1690c35ec8163a | |
parent | b75cf91b9a1077fc04468417ce87d33181295c62 [diff] |
[SYSTEMDS-2772] Add Autoencoder (2-layer) builtin DIA project WS2020/21.
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