Microsoft Microsoft Certifications DP-100 Questions & Answers

• Question 41:

  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.

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  Box 1: Accuracy

  Scenario: You want to configure hyperparameters in the model learning process to speed the learning phase by using hyperparameters. In addition, this configuration should cancel the lowest performing runs at each evaluation interval,

  thereby directing effort and resources towards models that are more likely to be successful.

  Box 2: R-Squared

• Question 42:

  HOTSPOT

  You plan to implement a two-step pipeline by using the Azure Machine Learning SDK for Python.

  The pipeline will pass temporary data from the first step to the second step.

  You need to identify the class and the corresponding method that should be used in the second step to access temporary data generated by the first step in the pipeline.

  Which class and method should you identify? To answer, select the appropriate options in the answer area.

  NOTE: Each correct selection is worth one point

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• Question 43:

  HOTSPOT

  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.

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  Box 1: 500

  For Random seed, type a value to use as seed for randomization. If you specify 0 (the default), a number is generated based on the system clock.

  A seed value is optional, but you should provide a value if you want reproducibility across runs of the same experiment.

  Here we must replicate the findings.

  Box 2: Mean Absolute Error

  Scenario: Given a trained model and a test dataset, you must compute the Permutation Feature Importance scores of feature variables. You need to set up the Permutation Feature Importance module to select the correct metric to investigate

  the model's accuracy and replicate the findings.

  Regression. Choose one of the following: Precision, Recall, Mean Absolute Error , Root Mean Squared Error, Relative Absolute Error, Relative Squared Error, Coefficient of Determination

  References:

  https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/permutation-feature-importance

• Question 44:

  HOTSPOT

  You train a model by using Azure Machine Learning. You use Azure Blob Storage to store production data.

  The model must be re-trained when new data is uploaded to Azure Blob Storage. You need to minimize development and coding.

  You need to configure Azure services to develop a re-training solution.

  Which Azure services should you use? To answer, select the appropriate options in the answer area.

  NOTE: Each correct selection is worth one point.

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• Question 45:

  HOTSPOT

  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.

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• Question 46:

  HOTSPOT

  You have a binary classifier that predicts positive cases of diabetes within two separate age groups.

  The classifier exhibits a high degree of disparity between the age groups. You need to modify the output of the classifier to maximize its degree of fairness across the age groups and meet the following requirements:

  1.

  Eliminate the need to retrain the model on which the classifier is based.

  2.

  Minimize the disparity between true positive rates and false positive rates across age groups.

  Which algorithm and panty constraint should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

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• Question 47:

  HOTSPOT

  You must use in Azure Data Science Virtual Machine (DSVM) as a compute target.

  You need to attach an existing DSVM to the workspace by using the Azure Machine Learning SDK for Python.

  How should you complete the following code segment? To answer, select the appropriate options in the answer area.

  NOTE: Each correct selection is worth one point.

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• Question 48:

  HOTSPOT

  You train a machine learning model by using Aunt Machine Learning.

  You use the following training script m Python to log an accuracy value.

  

  You must use a Python script to define a sweep job.

  You need to provide the primary metric and goal you want hyper parameter tuning to optimize.

  How should you complete the Python script? To answer select the appropriate options in the answer area

  NOTE: Each correct selection is worth one point.

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• Question 49:

  HOTSPOT

  You create an Azure Machine Learning dataset containing automobile price data. The dataset includes 10.000 rows and 10 columns. You use the Azure Machine Learning designer to transform the dataset by using an Execute Python Script

  component and custom code.

  The code must combine three columns to create a new column.

  You need to configure the code function.

  Which configurations should you use? To answer, select the appropriate options in the answer area.

  NOTE: Each correct selection is worth one point.

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• Question 50:

  HOTSPOT

  You use Azure Machine Learning to implement hyperparameter tuning with a Bandit early termination policy.

  The policy uses a slack_factor set to 01. an evaluation interval set to 1, and an evaluation delay set to b.

  You need to evaluate the outcome of the early termination policy

  What should you evaluate? To answer, select the appropriate options m the answer area.

  NOTE: Each correct selection is worth one point.

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