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DVC
Tool Details
Description
DVC (Data Version Control) is an open-source data and model versioning system bringing Git-like version control to machine learning projects.
It addresses a key MLOps challenge: managing large datasets and complex models alongside source code to ensure reproducibility.
DVC stores pointers in Git while actual data resides externally (cloud or local storage).
Key features include robust dataset versioning, experiment tracking for managing model runs, and ensuring full reproducibility of ML experiments.
By integrating with Git, DVC enables easy switching between data/model versions, enhanced collaboration, and transparent, auditable pipelines, essential for reliable, scalable AI systems.
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