Data Version Control (software)
DVC is a free and open-source, platform-agnostic version system for data, machine learning models, and experiments. It is designed to make ML models shareable, experiments reproducible, and to track versions of models, data, and pipelines. DVC works on top of Git repositories and cloud storage.
| Original author(s) | Dmitry Petrov |
|---|---|
| Developer(s) | Iterative.ai |
| Initial release | May 4, 2017; 5 years ago |
| Stable release | 2.30.0
/ October 10, 2022; 1 day ago |
| Repository | https://github.com/iterative/dvc |
| Written in | Python |
| Type | Machine Learning CLI |
| License | Apache - 2.0 |
| Website | dvc |
The first (beta) version of DVC 0.6 was launched in May 2017. In May 2020, DVC 1.0 was publicly released by Iterative.ai.
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