You are working on a project that requires organizing tracking information in a nested structure for better organization and clarity. Explain how you would create a nested Run in MLflow to achieve this, and discuss the benefits of using nested Runs for tracking organization.

Simulated

Create a new MLflow Run for each experiment and manually organize them into folders based on the experiment type.

4.2%

Use the MLflow UI to create a new Run and then create sub-Runs within that Run to create a nested structure.

27.1%

Create a new MLflow Run for each experiment and use tags to categorize them by experiment type.

10.4%

Use the MLflow Client API to create a new Run and then programmatically create sub-Runs within that Run to create a nested structure.

58.3%

Databricks Certified Machine Learning - Associate