Question

A data scientist runs an AutoML classification experiment through the Databricks AutoML UI to predict customer churn. After the experiment completes, they want to understand and customize the feature engineering and hyperparameters used by the top-performing model. What is the most direct way to accomplish this in Databricks AutoML?

Accepted Answer

Open the auto-generated notebook for the best trial from the AutoML experiment page, which contains the full source code for that model

Answer

Re-run the AutoML experiment with autologging enabled to capture the source code as an MLflow artifact

Answer

Download the registered model from Unity Catalog and decompile the serialized model file to inspect its code

Answer

Inspect the data exploration notebook, which contains the training code for every trial in the experiment