Exam DP-100 topic 2 question 119 discussion

Actual exam question from Microsoft's DP-100

Question #: 119
Topic #: 2

You manage an Azure Machine Learning workspace. You design a training job that is configured with a serverless compute.

The serverless compute must have a specific instance type and count.

You need to configure the serverless compute by using Azure Machine Learning Python SDK v2.

What should you do?

A. Specify the compute name by using the compute parameter of the command job.
B. Configure the tier parameter to Dedicated VM.
C. Initialize and specify the ResourceConfiguration class.
D. Initialize AmiCompute class with size and type specification.

Show Suggested Answer

Suggested Answer: C 🗳️

by AzureGeek79 at Sept. 30, 2024, 1:21 a.m.

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f82411e

1 week ago

Selected Answer: C

from azure.ai.ml.entities import CommandJob, ResourceConfiguration job = CommandJob( ... resources=ResourceConfiguration( instance_count=2, instance_type="Standard_DS3_v2" ) )

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ulg

4 months, 1 week ago

Selected Answer: C

To configure serverless compute with a specific instance type and count in Azure Machine Learning using the Python SDK v2, you need to use the ResourceConfiguration class.

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ulg

4 months, 1 week ago

https://learn.microsoft.com/en-us/azure/machine-learning/how-to-use-serverless-compute?view=azureml-api-2&tabs=python

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avinyc

5 months ago

Selected Answer: C

Correct answer should be ResourceConfiguration (C). The AmlCompute class is used for creating managed compute clusters, not for configuring serverless compute.

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Sadhak

6 months, 1 week ago

Selected Answer: D

https://learn.microsoft.com/en-us/python/api/azureml-core/azureml.core.compute.amlcompute(class)?view=azure-ml-py

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AzureGeek79

8 months, 1 week ago

Given answer is correct.

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