Question 131

You create a batch inference pipeline by using the Azure ML SDK. You run the pipeline by using the following code:
from azureml.pipeline.core import Pipeline
from azureml.core.experiment import Experiment
pipeline = Pipeline(workspace=ws, steps=[parallelrun_step])
pipeline_run = Experiment(ws, 'batch_pipeline').submit(pipeline)
You need to monitor the progress of the pipeline execution.
What are two possible ways to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
  • Question 132

    You use Azure Machine Learning to train and register a model.
    You must deploy the model into production as a real-time web service to an inference cluster named service-compute that the IT department has created in the Azure Machine Learning workspace.
    Client applications consuming the deployed web service must be authenticated based on their Azure Active Directory service principal.
    You need to write a script that uses the Azure Machine Learning SDK to deploy the model. The necessary modules have been imported.
    How should you complete the code? To answer, select the appropriate options in the answer area.

    Question 133

    You need to set up the Permutation Feature Importance module according to the model training requirements.
    Which properties should you select? To answer, select the appropriate options in the answer area.
    NOTE: Each correct selection is worth one point.

    Question 134

    Your Azure Machine Learning workspace has a dataset named real_estate_data. A sample of the data in the dataset follows.
    You want to use automated machine learning lo find the best regression model for predicting the price column. You need to configure an automated machine learning experiment using the Azure Machine Learning SDK. How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

    Question 135

    You create a multi-class image classification deep learning model that uses the PyTorch deep learning framework.
    You must configure Azure Machine Learning Hyperdrive to optimize the hyperparameters for the classification model.
    You need to define a primary metric to determine the hyperparameter values that result in the model with the best accuracy score.
    Which three actions must you perform? Each correct answer presents part of the solution.
    NOTE: Each correct selection is worth one point.