Exam AI-100 topic 4 question 5 discussion

Actual exam question from Microsoft's AI-100

Question #: 5
Topic #: 4

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.
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You create several API models in Azure Machine Learning Studio.
You deploy the models to a production environment.
You need to monitor the compute performance of the models.
Solution: You create environment files.
Does this meet the goal?

A. Yes
B. No

Show Suggested Answer

Suggested Answer: B 🗳️
You need to enable Model data collection.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-enable-data-collection

by awron_durat at Dec. 29, 2020, 6:12 p.m.

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rveney

2 years ago

B. No The solution mentioned does not meet the goal of monitoring the compute performance of the deployed API models in Azure Machine Learning Studio. Creating environment files alone does not provide monitoring capabilities for compute performance. Environment files in Azure Machine Learning Studio are used to define the dependencies and configurations required for running experiments and training models. They specify the software packages, Python versions, and other environment settings. To monitor the compute performance of the deployed API models, you would need to implement additional monitoring solutions. Azure Machine Learning Studio does not provide built-in monitoring features for compute performance. Instead, you could consider using Azure Monitor or other performance monitoring tools to track and analyze metrics related to the deployed models, such as CPU and memory usage, response times, and resource utilization.

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[Removed]

4 years, 3 months ago

This is incorrect answer "enable data collection" does not collect compute information. The correct answer is Monitor with Application Insights. https://docs.microsoft.com/en-us/azure/machine-learning/how-to-enable-app-insights#view-metrics-and-logs

upvoted 3 times

allanm

4 years, 1 month ago

The answer provided is correct. The explanation provided, is incorrect.

upvoted 2 times

claudiapatricia777

3 years, 7 months ago

Agree it is not app insights. I think the answer is the Data Drift Monitor because with this tool you can detect if the model is reducing accuracy over time. https://www.analyticsvidhya.com/blog/2021/10/mlops-and-the-importance-of-data-drift-detection/

upvoted 1 times

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awron_durat

4 years, 6 months ago

The answer provided is correct.

upvoted 2 times

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