Azure Data Scientists Associate Practice Exam

Where are model assets stored when MLflow autologging is enabled?

1. In the model folder under Outputs + logs

2. In the outputs folder under Outputs + logs

3. In the model folder under Metrics

4. In the artifacts folder

The correct answer is: In the model folder under Outputs + logs

When MLflow autologging is enabled, model assets are stored in the model folder under Outputs + logs. This is significant because MLflow is designed to track machine learning experiments, and enabling autologging allows it to automatically log parameters, metrics, and artifacts without requiring manual configuration. Autologging simplifies the process of capturing the necessary information to reproduce or analyze experiments. The model folder specifically provides a dedicated space for storing artifacts related to the model's training and deployment. This centralized storage under Outputs + logs ensures that all model-related data is organized and accessible for review or future use. The choice indicating that assets are stored in other specified folders does not accurately reflect the default behavior of MLflow autologging.