Databricks Machine Learning Associate Question 463
Select 4You are a data scientist using MLflow to manage your machine learning experiments in Databricks. After running several experiments, you navigate to the MLflow UI to analyze the results. Which of the following pieces of information can you find directly in the MLflow UI?
- A
The parameters used for each experiment run
- B
The hyperparameter tuning strategy used for the model
- C
The model's performance metrics such as accuracy or loss
- D
The source code version or Git commit associated with the experiment
- E
The deployment endpoint of the registered model
- F
The duration of each experiment run
Show answer and explanation
Correct answers: A, C, D, F
Explanation
The MLflow UI provides detailed information about experiment runs, such as parameters, metrics, source code version, and run duration. However, it does not display information unrelated to the experiment tracking, such as hyperparameter tuning strategies or deployment endpoints, which are handled outside the experiment tracking interface.
- A. Correct.
The MLflow UI displays the parameters used for each experiment run, which are logged during the training process.
- B. Incorrect.
MLflow does not log or display the hyperparameter tuning strategy, as it is not explicitly recorded unless manually logged.
- C. Correct.
Model performance metrics such as accuracy, loss, and others are logged and can be viewed in the MLflow UI.
- D. Correct.
The MLflow UI shows the source code version or Git commit hash if it is logged during the experiment, such as through the use of MLflow's autologging or manual logging.
- E. Incorrect.
The deployment endpoint of a registered model is not displayed in the experiment tracking UI but is available in the Model Registry.
- F. Correct.
The MLflow UI includes information about the duration of each experiment run, which is logged automatically.