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 an Azure Databricks hosted tracking server. It also includes instructions for viewing the logged results in the MLflow tracking UI.
To deploy your trained model using Mosaic AI Model Serving, see Model serving with Azure Databricks.