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Exam AI-102 topic 3 question 39 discussion

Actual exam question from Microsoft's AI-102
Question #: 39
Topic #: 3
[All AI-102 Questions]

You train a Conversational Language Understanding model to understand the natural language input of users.

You need to evaluate the accuracy of the model before deploying it.

What are two methods you can use? Each correct answer presents a complete solution.

NOTE: Each correct selection is worth one point.

  • A. From the language authoring REST endpoint, retrieve the model evaluation summary.
  • B. From Language Studio, enable Active Learning, and then validate the utterances logged for review.
  • C. From Language Studio, select Model performance.
  • D. From the Azure portal, enable log collection in Log Analytics, and then analyze the logs.
Show Suggested Answer Hide Answer
Suggested Answer: AC 🗳️

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ziggy1117
Highly Voted 1 year, 7 months ago
Selected Answer: AC
agree with SmallFire: Active Learning cannot be initiated prior to the deployment of the model. The primary purpose of the 'Active Learning' feature is to leverage actual user interaction data to enhance the model's understanding capabilities. This is a continuous learning and optimization process that takes place after the model has been deployed and put into actual use. so the answer is AC.
upvoted 11 times
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anto69
Most Recent 4 months, 4 weeks ago
Selected Answer: AC
A-C ChatGPT still think that B is better than A, but this time I'm not agree
upvoted 1 times
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reiwanotora
6 months, 3 weeks ago
Selected Answer: AC
REST endpoint select Model performance
upvoted 1 times
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HaraTadahisa
6 months, 3 weeks ago
Selected Answer: AC
I say this answer is A and C.
upvoted 1 times
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reigenchimpo
7 months ago
Selected Answer: AC
AC is answer.
upvoted 1 times
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takaimomoGcup
7 months, 3 weeks ago
Selected Answer: AC
REST and model performance.
upvoted 2 times
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evangelist
11 months, 2 weeks ago
Selected Answer: AC
A. From the language authoring REST endpoint, retrieve the model evaluation summary. This summary typically includes metrics like precision, recall, and accuracy, which are crucial for evaluating the effectiveness of a language understanding model. C. From Language Studio, select Model performance. In Language Studio, the Model performance section typically provides detailed analytics about the model's performance, including various metrics and possibly confusion matrices.
upvoted 3 times
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rdemontis
1 year, 2 months ago
Selected Answer: AC
IMHO correct answers are: A. --> https://learn.microsoft.com/en-us/rest/api/language/conversational-analysis-authoring/get-model-evaluation-summary?view=rest-language-2023-04-01&tabs=HTTP C. --> https://learn.microsoft.com/en-us/azure/ai-services/language-service/conversational-language-understanding/how-to/view-model-evaluation?tabs=Language-studio%2Cmodel-performance
upvoted 2 times
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sl_mslconsulting
1 year, 2 months ago
Selected Answer: AC
If you look closely, you can see that the Model performance feature in Language Studio is about evaluating the performance of the model using test data as opposed to active learning which is using the real data from users’ interactions, which you couldn’t do prior to the deployment. My only pet peeve is that rest endpoint never works for me - always giving me the 404 no matter what.
upvoted 1 times
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jangotango
1 year, 3 months ago
AC are correct - https://learn.microsoft.com/en-us/rest/api/language/2022-10-01-preview/text-analysis-authoring/get-model-evaluation-summary?tabs=HTTP
upvoted 2 times
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zellck
1 year, 6 months ago
Selected Answer: AC
AC is the answer. https://learn.microsoft.com/en-us/azure/cognitive-services/language-service/conversational-language-understanding/how-to/view-model-evaluation?tabs=Language-studio%2Cmodel-performance
upvoted 4 times
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EliteAllen
1 year, 6 months ago
Selected Answer: BC
B. Active Learning in Language Studio is a feature that helps improve the performance of your model by suggesting utterances for you to review and label. This can help you evaluate the accuracy of your model by seeing how it performs on these suggested utterances. C. The Model performance feature in Language Studio provides a detailed report on the performance of your model, including precision, recall, and F1 score. This can give you a good indication of the accuracy of your model. Option A is incorrect because the language authoring REST endpoint does not provide a model evaluation summary.
upvoted 2 times
hawkzey
1 year, 4 months ago
B is not correct as you cant not do active learning on a model that is not yet deployed
upvoted 2 times
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SmallFire
1 year, 7 months ago
Active Learning cannot be initiated prior to the deployment of the model. The primary purpose of the 'Active Learning' feature is to leverage actual user interaction data to enhance the model's understanding capabilities. This is a continuous learning and optimization process that takes place after the model has been deployed and put into actual use. so the answer is AC.
upvoted 4 times
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sheldon73
1 year, 7 months ago
Selected Answer: BC
Google Bard Answer : Sure, here are two methods you can use to evaluate the accuracy of a Conversational Language Understanding model before deploying it: From Language Studio, select Model performance. This will show you a summary of the model's performance, including the F1 score, precision, and recall. From Language Studio, enable Active Learning, and then validate the utterances logged for review. This will allow you to manually review utterances that the model has misclassified, and then retrain the model with the corrected data. Here are the correct answers to your question: C. From Language Studio, select Model performance. B. From Language Studio, enable Active Learning, and then validate the utterances logged for review.
upvoted 1 times
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