Feature engineering with scikit-learn
The example notebook on this page illustrates how to use scikit-learn on Azure Databricks for feature engineering.
Use scikit-learn with MLflow integration on Azure Databricks
This notebook shows a complete end-to-end example of loading data, training a model, distributed hyperparameter tuning, and model inference. It also illustrates how to use MLflow and the model registry.
If your workspace is enabled for Unity Catalog, use this version of the notebook:
Use scikit-learn with MLflow integration on Databricks (Unity Catalog)
If your workspace is not enabled for Unity Catalog, use this version of the notebook:
Use scikit-learn with MLflow integration on Databricks
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