Free DP-100 Exam Braindumps
Designing and Implementing a Data Science Solution on Azure Questions 171–175 (page: 36)

DRAG DROP (Drag and Drop is not supported)

You have an Azure Machine Learning workspace.
You plan to use the terminal to configure a compute instance to run a notebook.
You need to add a new R kernel to the compute instance.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.

HOTSPOT (Drag and Drop is not supported)

You manage an Azure Machine Learning workspace named Workspace1 and an Azure Blob Storage accessed by using the URL https://storage1.blob.core.windows.net/data1.
You plan to create an Azure Blob datastore in Workspace1. The datastore must target the Blob Storage by using Azure Machine Learning Python SDK v2. Access authorization to the datastore must be limited to a specific amount of time.
You need to select the parameters of the AzureBlobDatastore class that will point to the target datastore and authorize access to it.
Which parameters should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

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 manage an Azure Machine Learning workspace. The development environment for managing the workspace is configured to use Python SDK v2 in Azure Machine Learning Notebooks.
A Synapse Spark Compute is currently attached and uses system-assigned identity.
You need to use Python code to update the Synapse Spark Compute to use a user-assigned identity.
Solution: Pass the UserAssignedIdentity class object to the SynapseSparkCompute class.
Does the solution meet the goal?

DRAG DROP (Drag and Drop is not supported)

You have an Azure Machine Learning workspace named WS1.
You plan to use WS1 to train two models named model1 and model2. For model1, you plan to use automated machine learning. For model2, you plan to use Azure Machine Learning designer.
You need to determine the compute targets you should use to train each model. Your solution must ensure the following:
• The compute target for model1 supports auto-shutdown/auto-start based on a schedule.
• The compute target for model2 supports the use of low-priority Azure Virtual Machines.
Which compute targets should you use? To answer, move the appropriate compute targets to the correct model. You may use each compute target once, more than once, or not at all. You may need to move the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

You manage an Azure Machine Learning Workspace named Workspase1 and an Azure Files share named Share1.
You plan to create an Azure Files datastore in Workspace1 to target Share1.
You need to configure permanent access to Share1 from the Azure Files datastore.
Which authorization method should you use?