Open-source data and model versioning for ML workflows
DVC (Data Version Control) is an open-source tool for versioning data and ML models alongside code in Git. It tracks large files, datasets, and model artifacts without storing them in Git, using cloud storage as a backend. DVC pipelines define reproducible ML workflows that can be versioned, shared, and reproduced. Essential for teams that need Git-like workflows for ML assets.
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