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Exam AI-102 topic 3 question 2 discussion

Actual exam question from Microsoft's AI-102
Question #: 2
Topic #: 3
[All AI-102 Questions]

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 develop an application to identify species of flowers by training a Custom Vision model.
You receive images of new flower species.
You need to add the new images to the classifier.
Solution: You add the new images, and then use the Smart Labeler tool.
Does this meet the goal?

  • A. Yes
  • B. No
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️

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TheB
Highly Voted 3 years, 5 months ago
The answer is correct.
upvoted 15 times
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sl_mslconsulting
Highly Voted 1 year, 2 months ago
Selected Answer: B
The answer is B is because the limitations of the smart labeler: You should only request suggested tags for images whose tags have already been trained on once. Don't get suggestions for a new tag that you're just beginning to train. You are given new images of species that have not been seen by the model how can you expect it to suggest what they are? Also you can train the model right in the smart labeler: check the workflow and the limitations in the doc. https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/suggested-tags
upvoted 10 times
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9cc71b6
Most Recent 3 weeks, 3 days ago
Selected Answer: B
Answer is B
upvoted 1 times
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rdemontis
1 year, 1 month ago
Selected Answer: B
Answer and explanation are correct. https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/suggested-tags
upvoted 1 times
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james2033
1 year, 3 months ago
Selected Answer: B
Smart Labeler for suggestion https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/suggested-tags
upvoted 1 times
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zellck
1 year, 5 months ago
Selected Answer: B
B is the answer. https://learn.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/suggested-tags Smart Labeler will generate suggested tags for images. This lets you label a large number of images more quickly when you're training a Custom Vision model. When you tag images for a Custom Vision model, the service uses the latest trained iteration of the model to predict the labels of new images. It shows these predictions as suggested tags, based on the selected confidence threshold and prediction uncertainty. You can then either confirm or change the suggestions, speeding up the process of manually tagging the images for training.
upvoted 1 times
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hens
1 year, 7 months ago
chat gpt " ChatGPT A. Yes. Using the Smart Labeler tool is a valid way to train a Custom Vision model with new images. It allows the user to label images more efficiently by using an active learning approach that selects images that will have the highest impact on the model's performance."
upvoted 2 times
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ExamGuruBhai
2 years, 4 months ago
retrain model so answer is B
upvoted 1 times
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Eltooth
2 years, 4 months ago
Selected Answer: B
B is correct answer : No. Instead the model need to be extended and retrained (Udemy answer).
upvoted 4 times
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hendriktytgatpwc
2 years, 9 months ago
answer is correct
upvoted 1 times
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sumanshu
2 years, 11 months ago
Label + Retrain
upvoted 2 times
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azurelearner666
3 years, 5 months ago
correct! retraining is necesary!
upvoted 5 times
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