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Exam DP-100 topic 2 question 50 discussion

Actual exam question from Microsoft's DP-100
Question #: 50
Topic #: 2
[All DP-100 Questions]

You create an Azure Machine Learning compute resource to train models. 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.
What are three possible ways to achieve this goal? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.

  • A. Use the Azure Machine Learning studio.
  • B. Run the update method of the AmlCompute class in the Python SDK.
  • C. Use the Azure portal.
  • D. Use the Azure Machine Learning designer.
  • E. Run the refresh_state() method of the BatchCompute class in the Python SDK.
Show Suggested Answer Hide Answer
Suggested Answer: ABC 🗳️
A: You can manage assets and resources in the Azure Machine Learning studio.
B: The update(min_nodes=None, max_nodes=None, idle_seconds_before_scaledown=None) of the AmlCompute class updates the ScaleSettings for this
AmlCompute target.
C: To change the nodes in the cluster, use the UI for your cluster in the Azure portal.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.compute.amlcompute(class)
by dev2dev at March 17, 2021, 6:36 a.m.

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Haet
Highly Voted 3 years, 6 months ago
Answer is correct A,B,C. I have verified it
upvoted 23 times
chaudha4
3 years, 6 months ago
Can you elaborate on "C". There is no access to the cluster from Azure portal. Where do you see it ?
upvoted 3 times
SaudMeethal
3 years, 5 months ago
Azure portal is unlikely to do this and refresh_state() method of the BatchCompute also seems to be incorrect. In designer there is an option to create a new CC with the specifications we require, but not sure if it can be considered as reconfiguration as we're simply creating another resource.
upvoted 4 times
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levm39
Highly Voted 3 years, 4 months ago
Answer is A,B C was possible in the past, they removed the option to manage compute instance for ML from the portal. E is incorrect
upvoted 17 times
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NullVoider_0
Most Recent 8 months, 3 weeks ago
On exam 12-02-2024.
upvoted 1 times
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Awooga
8 months, 4 weeks ago
On exam 2024-02-06
upvoted 1 times
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phdykd
1 year, 9 months ago
A. Use the Azure Machine Learning studio. C. Use the Azure portal. D. Use the Azure Machine Learning designer.
upvoted 2 times
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therealola
2 years, 4 months ago
On exam 18-06-22
upvoted 1 times
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ning
2 years, 5 months ago
Only know A and B ...
upvoted 2 times
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JTWang
2 years, 6 months ago
on exam 04/22/2022
upvoted 2 times
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synapse
2 years, 7 months ago
Selected Answer: ABC
A B C. Given answer is correct
upvoted 1 times
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piyu18
2 years, 10 months ago
I think its correct, as we can access ml compute from cli and we can connect with cli from azure portal
upvoted 2 times
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VJPrakash
3 years, 2 months ago
on exam in August 2021
upvoted 1 times
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slash_nyk
3 years, 4 months ago
How you can do if from Machine Learning Studio ?
upvoted 2 times
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scipio
3 years, 5 months ago
Cannot be E. BatchCompute is an attach resource, and refresh_state() is "This method updates the properties based on the current state of the corresponding cloud object. This is primarily used for manual polling of compute state." Just a refresh. I agree though that C is strange, except to use the portal to access the ML Studio. https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.compute.batchcompute?view=azure-ml-py#refresh-state--
upvoted 4 times
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chaudha4
3 years, 6 months ago
The correct answer is A, B and E. You cannot do it from portal.
upvoted 7 times
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dev2dev
3 years, 7 months ago
I dont see from where we can resize the culuster size from portal except that from the ml workspace we click on studio link and change from there
upvoted 5 times
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dev2dev
3 years, 7 months ago
I dont see from where we can resize the culuster size from portal except that from the workspace we click on studio link
upvoted 2 times
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C (25%)
B (20%)
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