DVC Data Version Control Architecture Overview | #mlops #dvc #machinelearning

DVC (Data Version Control) for machine learning is an open-source tool that is used to manage and track changes in the data used during the machine learning development process.

It provides a system for version controlling data sets in a similar way to how software developers version control code. With DVC, it is possible to version control data sets, track data lineage, and collaborate with team members. It helps in maintaining a record of data used for training, testing, and evaluating models, which is crucial for reproducing results and sharing findings with others.

Additionally, it integrates with popular technologies used in machine learning such as Git and cloud storage services.

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