Overview
DVC (Data Version Control) is an open-source version control system for machine learning projects. It extends Git to handle large datasets and machine learning models, enabling teams to track changes, reproduce experiments, and collaborate effectively. DVC manages data in a separate storage system (like S3, GCS, or Azure Blob Storage) while keeping metadata in Git. This approach allows for versioning of data without bloating the Git repository. It provides features like data pipelines, experiment tracking, and model management. DVC is designed for data scientists, machine learning engineers, and AI teams looking to apply software engineering best practices to their data science workflows.