| commit | c61e54e92429a1a138ae1221cec940ee95ecad08 | [log] [tgz] |
|---|---|---|
| author | Duc Thai Vu <thaivd1309@gmail.com> | Mon Apr 15 11:57:39 2024 +0200 |
| committer | Sebastian Baunsgaard <baunsgaard@apache.org> | Mon Apr 15 12:48:26 2024 +0200 |
| tree | dad8a26a85614ec8c697e082753b4f4a4ba6cd1f | |
| parent | 4073206a1a46cfc6e03628ae699f36f9174c664f [diff] |
[SYSTEMDS-3426] Python NN Builtin (Affine,Relu) This commit adds the new interface for easy usage of our neural network in python. The design take inspiration from other neural network frameworks. This specific commit contains the building blocks of Affine and Relu. Closes #1848 Closes #1929 Co-authored-by: Duc Thai Vu <thaivd1309@gmail.com> Co-authored-by: Rahul Joshi <rahuljoshi8227@gmail.com>
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
