commit | 13d4db76948b141fad82a120d2068c1ca4560993 | [log] [tgz] |
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author | Sebastian Baunsgaard <baunsgaard@apache.org> | Tue Jan 30 14:27:47 2024 +0100 |
committer | Sebastian Baunsgaard <baunsgaard@apache.org> | Tue Jan 30 14:28:03 2024 +0100 |
tree | 0efa1c50f77f13548525dbbd102699d3484f4cb9 | |
parent | 75cf454e282100be722a3dc9805d941dc16ee770 [diff] |
[MINOR] Add extra safety checks for as.frame
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