Track scikit-learn model training with MLflow

This notebook is based on the MLflow scikit-learn diabetes tutorial.

The notebook shows how to use MLflow to track the model training process, including logging model parameters, metrics, the model itself, and other artifacts like plots to a Databricks hosted tracking server. It also includes instructions for viewing the logged results in the MLflow tracking UI.

The following guides describe deployment options for your trained model:

• Deploy your model using Model serving with Databricks

• scikit-learn model deployment on SageMaker

MLflow scikit-learn model training notebook

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