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Data Version Control · DVC
DVC is an open-source tool for version control in data science and machine learning, helping you track data, models, and experiments like with Git.
Version control for data and ML experiments
DVC (Data Version Control) is an open-source platform designed for data scientists and machine learning teams who need to manage and version large datasets, models, and experiments. It works alongside Git to bring version control to files that are too big or change too often for traditional code repositories, making your workflows reproducible and organized.
With DVC, you can track every step of your ML projects, from data storage to model training, and easily share results with your team. The platform streamlines collaboration, helps you compare experiment results, and lets you restore previous states when needed. If you want to keep your data and models in sync with your code and make your AI projects more manageable, DVC is a practical and user-friendly solution.
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