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DP-100 Questions Bank

Page: 8 / 11
Total 428 questions

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

Question 29

You are developing code to analyse a dataset that includes age information for a large group of diabetes patients. You create an Azure Machine Learning workspace and install all required libraries. You set the privacy budget to 1.0).

You must analyze the dataset and preserve data privacy. The code must run twice before the privacy budget is depleted.

You need to complete the code.

Which values should you use? To answer, select the appropriate options m the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 30

You create an experiment in Azure Machine Learning Studio. You add a training dataset that contains 10,000 rows. The first 9,000 rows represent class 0 (90 percent).

The remaining 1,000 rows represent class 1 (10 percent).

The training set is imbalances between two classes. You must increase the number of training examples for class 1 to 4,000 by using 5 data rows. You add the Synthetic Minority Oversampling Technique (SMOTE) module to the experiment.

You need to configure the module.

Which values should you use? To answer, select the appropriate options in the dialog box in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Question 31

You create an Azure Machine Learning workspace. The workspace contains a dataset named sample.dataset, a compute instance, and a compute cluster. You must create a two-stage pipeline that will prepare data in the dataset and then train and register a model based on the prepared data. The first stage of the pipeline contains the following code:

You need to identify the location containing the output of the first stage of the script that you can use as input for the second stage. Which storage location should you use?

Options:

A.

workspaceblobstore datastore

B.

workspacefi lest ore datastore

C.

compute instance

Question 32

You create an Azure Machine Learning model to include model files and a scorning script. You must deploy the model. The deployment solution must meet the following requirements:

• Provide near real-time inferencing.

• Enable endpoint and deployment level cost estimates.

• Support logging to Azure Log Analytics.

You need to configure the deployment solution.

What should you configure? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

Options:

Page: 8 / 11
Total 428 questions