DVC brings software engineering best practices to data, AI/ML, and data science teams using a Git-like model for data version control.
DVC (Data Version Control) is an open-source version control system for machine learning projects. It extends Git to handle large files, datasets, machine learning models, and metrics, enabling data scientists and machine learning engineers to version their data alongside their code. DVC allows users to track changes to data, reproduce experiments, and collaborate effectively on data science projects. It focuses on data versioning, experiment management, and reproducibility, making it easier to manage complex ML workflows. By integrating seamlessly with Git, DVC provides a familiar interface and workflow for data version control, making it accessible to both individual data scientists and enterprise AI teams.
DVC (Data Version Control) is an open-source version control system for machine learning projects.
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Manage data and machine learning models with version control, making AI/ML projects reproducible and collaborative.
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