About
Open-source version control for ML projects. Manage datasets, ML pipelines, and experiments with Git-like workflows.
Features
- Git-based versioning: lightweight .dvc files point to data stored in remote storage
- Pipeline management: define multi-step ML workflows in dvc.yaml files
- Experiment tracking: log metrics, hyperparameters, and plots directly in the repo
- Cache mechanism: reuse unchanged pipeline outputs to speed up iteratons
- Remote storage abstraction: works with local, S3, GCS, Azure, SSH, and HDFS drives
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