From Databricks to Container
Laura explains how to operationalize a model from Azure Databricks to a container using ML Flow and Docker APIs. She highlights the ease of grouping the training set, PY files, and source data together within the notebook framework, and utilizing Azure DevOps for a seamless DevOps pipeline.In this clip
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