Free DP-100 Exam Braindumps
Designing and Implementing a Data Science Solution on Azure Questions 146–150 (page: 31)

HOTSPOT (Drag and Drop is not supported)

You are creating data wrangling and model training solutions in an Azure Machine Learning workspace.
You must use the same Python notebook to perform both data wrangling and model training.
You need to use the Azure Machine Learning Python SDK v2 to define and configure the Synapse Spark pool asynchronously in the workspace as dedicated compute.
How should you complete the code segment? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

HOTSPOT (Drag and Drop is not supported)

You manage an Azure Machine Learning workspace named workspace1 by using the Python SDK v2.
You must register datastores in workspace1 for Azure Blob and Azure Data Lake Gen2 storage to meet the following requirements:
• Data scientists accessing the datastore must have the same level of access.
• Access must be restricted to specified containers or folders.
You need to configure a security access method used to register the Azure Blob and Azure Data Lake Gen2 storage in workspace1.
Which security access method should you configure? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

DRAG DROP (Drag and Drop is not supported)

You create an Azure Machine Learning workspace and an Azure Synapse Analytics workspace with a Spark pool. The workspaces are contained within the same Azure subscription.
You must manage the Synapse Spark pool from the Azure Machine Learning workspace.
You need to attach the Synapse Spark pool in Azure Machine Learning by using the Python SDK v2.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

You manage an Azure Machine Learning workspace.
You need to define an environment from a Docker image by using the Azure Machine Learning Python SDK v2.
Which parameter should you use?

You create an Azure Machine Learning managed compute resource. The compute resource is configured as follows:
• Minimum nodes: 2
• Maximum nodes: 4
You must decrease the minimum number of nodes and increase the maximum number of nodes to the following values:
• Minimum nodes: 0
• Maximum nodes: 8
You need to reconfigure the compute resource.
Which three methods can you use? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.