Question 281

You create a script that trains a convolutional neural network model over multiple epochs and logs the validation loss after each epoch. The script includes arguments for batch size and learning rate.
You identify a set of batch size and learning rate values that you want to try.
You need to use Azure Machine Learning to find the combination of batch size and learning rate that results in the model with the lowest validation loss.
What should you do?
  • Question 282

    You need to configure the Permutation Feature Importance module for the model training requirements.
    What should you do? To answer, select the appropriate options in the dialog box in the answer area.
    NOTE: Each correct selection is worth one point.

    Question 283

    You use Azure Machine Learning to implement hyperparameter tuning for an Azure ML Python SDK v2-based model training.
    Training runs must terminate when the primary metric is lowered by 25 percent or more compared to the best performing run.
    You need to configure an early termination policy to terminate training jobs.
    Which values should you use? To answer, select the appropriate options in the answer area.
    NOTE: Each correct selection is worth one point.

    Question 284

    You have an Azure Machine learning workspace. The workspace contains a dataset with data in a tabular form.
    You plan to use the Azure Machine Learning SDK for Python vl to create a control script that will load the dataset into a pandas dataframe in preparation for model training The script will accept a parameter designating the dataset You need to complete the script.
    How should you complete the script? To answer, select the appropriate options in the answer area.
    NOTE: Each correct selection is worth one point.

    Question 285

    You are using the Hyperdrive feature in Azure Machine Learning to train a model.
    You configure the Hyperdrive experiment by running the following code:

    For each of the following statements, select Yes if the statement is true. Otherwise, select No.
    NOTE: Each correct selection is worth one point.