| commit | fe4b4a29fbefc61be36d18e6c14e30e67b6566ab | [log] [tgz] |
|---|---|---|
| author | e-strauss <lathancer@gmx.de> | Wed Sep 04 19:15:38 2024 +0200 |
| committer | Sebastian Baunsgaard <baunsgaard@apache.org> | Wed Sep 04 19:15:38 2024 +0200 |
| tree | 0db3613bf3129e60119178222386f1057a63599d | |
| parent | 7daa5908e5c771c35445dc7f434b75dcccc077ab [diff] |
[MINOR] Python API: manual generator option This commit adds a manual option for adding algorithm builtin files to the python algorithms folder. Also contained is the auto generated builtin for sliceLine. Closes #2094
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.
| Resource | Links |
|---|---|
| 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
