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| <Project rdf:about="https://systemds.apache.org/"> |
| <created>2023-09-13</created> |
| <license rdf:resource="https://spdx.org/licenses/Apache-2.0" /> |
| <name>Apache SystemDS</name> |
| <homepage rdf:resource="https://systemds.apache.org/" /> |
| <asfext:pmc rdf:resource="https://systemds.apache.org" /> |
| <shortdesc>An open source ML system for the end-to-end data science lifecycle </shortdesc> |
| <description>Apache SystemDS is a machine learning (ML) system for the end-to-end data science lifecycle from data preparation and cleaning, over efficient ML model training, to scoring and debugging. ML algorithms or pipelines are specified in a high-level language with R-like syntax, or related Python and Java APIs, and the system automatically generates hybrid runtime plans of local, in-memory operations and distributed operations on Apache Spark.</description> |
| <bug-database rdf:resource="https://issues.apache.org/jira/secure/Dashboard.jspa?selectPageId=12335852" /> |
| <mailing-list rdf:resource="https://systemds.apache.org/community" /> |
| <download-page rdf:resource="https://systemds.apache.org/download" /> |
| <programming-language>C++</programming-language> |
| <programming-language>Java</programming-language> |
| <programming-language>Python</programming-language> |
| <programming-language>R</programming-language> |
| <category rdf:resource="https://projects.apache.org/category/big-data" /> |
| <category rdf:resource="https://projects.apache.org/category/data-engineering" /> |
| <release> |
| <Version> |
| <name>Apache SystemDS 3.1.0</name> |
| <created>2023-03-13</created> |
| <revision>3.1.0</revision> |
| </Version> |
| </release> |
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