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Passed Exam Today DP-100

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Total 476 questions

Designing and Implementing a Data Science Solution on Azure Questions and Answers

Question 45

You are performing a filter based feature selection for a dataset 10 build a multi class classifies by using Azure Machine Learning Studio.

The dataset contains categorical features that are highly correlated to the output label column.

You need to select the appropriate feature scoring statistical method to identify the key predictors. Which method should you use?

Options:

A.

Chi-squared

B.

Spearman correlation

C.

Kendall correlation

D.

Person correlation

Question 46

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You have an Azure Machine Learning workspace. You connect to a terminal session from the Notebooks page in Azure Machine Learning studio.

You plan to add a new Jupyter kernel that will be accessible from the same terminal session.

You need to perform the task that must be completed before you can add the new kernel.

Solution: Delete the Python 3.6 - AzureML kernel.

Does the solution meet the goal?

Options:

A.

Yes

B.

No

Question 47

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.

Options:

A.

Set the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to maximize.

B.

Add code to the bird_classifier_train.py script to calculate the validation loss of the model and log it as a float value with the key loss.

C.

Set the primary_metric_goal of the estimator used to run the bird_classifier_train.py script to minimize.

D.

Set the primary_metric_name of the estimator used to run the bird_classifier_train.py script to accuracy.

E.

Set the primary_metric_name of the estimator used to run the bird_classifier_train.py script to loss.

F.

Add code to the bird_classifier_train.py script to calculate the validation accuracy of the model and log it as a float value with the key accuracy.

Question 48

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.

NOTE: Each correct selection is worth one point.

Options:

Page: 12 / 16
Total 476 questions