Systemds
An open source ML system for the end-to-end data science lifecycle
**Overview:** Apache SystemDS is an open-source machine learning (ML) system for the end-to-end data science lifecycle from data preparation and cleaning, over efficient ML model training, to debugging and serving. ML algorithms or pipelines are specified in a high-level language with R-like syntax or related Python and Java APIs (with many builtin primitives), and the system automatically generates hybrid runtime plans of local, in-memory operations and distributed operations on Apache Spark. A... The project is written primarily in Java, distributed under the Apache License 2.0 license, first published in 2015. It has gained significant community traction with 1,091 stars and 541 forks on GitHub. Key topics include: dml, java, python, systemds.
Apache SystemDS
Overview: Apache SystemDS is an open-source machine learning (ML) system for the end-to-end
data science lifecycle from data preparation and cleaning, over efficient ML model training,
to debugging and serving. ML algorithms or pipelines are specified in a high-level language
with R-like syntax or related Python and Java APIs (with many builtin primitives), and the
system automatically generates hybrid runtime plans of local, in-memory operations and distributed
operations on Apache Spark. Additional backends exist for GPUs and federated learning.
| 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
Contributors
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