Data Version Control · DVC

What is Data Version Control · DVC?

Data Version Control (DVC) is an open-source version control system designed for Data Science and Machine Learning projects. It provides a Git-like experience to organize data, models, and experiments, enabling reproducible workflows and collaboration.

How to use Data Version Control · DVC?

DVC allows you to manage and version large data and model files alongside your code by connecting to cloud storage. You can declare dependencies and outputs at each step to build reproducible pipelines and track experiments in Git, compare results, and restore experiment states.

Data Version Control · DVC’s Core Features

Data and model versioning Reproducible ML pipelines Experiment tracking Integration with Git and cloud storage

Data Version Control · DVC’s Use Cases

• Managing large data files in machine learning projects
• Creating reproducible end-to-end ML pipelines
• Tracking and comparing different experiment results
• Collaborating on data science projects with version control