Databricks Machine Learning Associate exam dumps

Databricks Machine Learning Associate practice question 109 of 656

Databricks Certified Machine Learning Associate. Associate level, Databricks. Free question with the correct answer and a full explanation.

Databricks Machine Learning Associate Question 109

Select 3

You are training a machine learning model in Databricks and want to track different components of your workflow using MLflow. During the training process, you decide to create a nested run to organize tracking for a hyperparameter tuning step within the main experiment run. Which of the following statements about nested runs is correct?

  1. A

    Nested runs allow you to group related tasks, such as hyperparameter tuning, under a parent run for better organization.

  2. B

    To create a nested run, you must explicitly set the nested parameter to True when starting the child run.

  3. C

    Nested runs are automatically created whenever you log metrics or parameters in a loop within a single parent run.

  4. D

    You can view nested runs in the MLflow UI, where they are displayed hierarchically under the parent run.

  5. E

    Nested runs require a separate MLflow experiment compared to the parent run.

Show answer and explanation

Correct answers: A, B, D

Explanation

Nested runs in MLflow are a powerful feature for organizing complex workflows, such as hyperparameter tuning or multi-step pipelines, within a single experiment. To create a nested run, you must explicitly set the nested=True parameter when starting the child run. These runs are displayed hierarchically in the MLflow UI for better tracking and analysis. They do not require a separate experiment and are not created automatically.

  • A. Correct.

    Correct: Nested runs are designed to help organize related tasks under a parent run, such as tracking experiments with multiple sub-tasks like hyperparameter tuning.

  • B. Correct.

    Correct: When starting a new run using mlflow.start_run, you must explicitly set the nested=True parameter to indicate that it is a nested run.

  • C. Incorrect.

    Incorrect: Nested runs are not created automatically. You must explicitly define them by starting a new run with the nested=True parameter.

  • D. Correct.

    Correct: MLflow UI supports nested runs and displays them hierarchically under their parent run, making it easier to analyze related tasks.

  • E. Incorrect.

    Incorrect: Nested runs do not require a separate experiment. They exist within the same MLflow experiment as the parent run.

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