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-Data Science Version Control or DVC is an open-source tool for data science and
-machine learning projects. With a simple and flexible Git-like architecture and
-interface it helps data scientists:
-* manage machine learning models - versioning, including data sets and
- transformations (scripts) that were used to generate models;
-* make projects reproducible;
-* make projects shareable;
-* manage experiments with branching and metrics tracking.
-
-It aims to replace tools like Excel and Docs that are being commonly used as a
-knowledge repo and a ledger for the team, ad-hoc scripts to track and move
-deploy different model versions, ad-hoc data file suffixes and prefixes.