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In this demo, we are showcasing a new Data Science workflow where we create a CI pipeline to explore different configurations of a model, use MLflow to store this information on GitLab, and then train a new model version to be shared on the application. For feedback, reach out on the model registry epic: https://gitlab.com/groups/gitlab-org ...
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