DagsHub

Meet DagsHub

DagsHub keeps machine-learning datasets, experiments, and models connected. Teams can bring in multiple data sources, inspect and query multimodal examples, and annotate material for training or evaluation. Experiment tracking records runs and makes their results available for comparison, including workflows that use MLflow.

Model management tracks versions and their lineage back to source data, so a team can review how a model was produced before choosing one for deployment. Integrations connect existing storage and machine-learning tools, with cloud and on-premises options for enterprise use. The workspace puts the dataset, the run, and the resulting model within the same project context.