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Answer: Set up alerts for high error rates or performance degradation.
Setting up alerts for high error rates or performance degradation is an effective approach for monitoring the model's performance and detecting potential issues over time. This allows you to quickly identify and address any problems that may arise, such as concept drift, data quality issues, or model misconfigurations. While periodically retraining the model with new data, monitoring the input data distribution, and manually reviewing predictions can also be useful, setting up alerts provides a more proactive and automated way to monitor the model's performance in production. It enables you to take immediate action when needed and maintain the model's reliability and accuracy over time.
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You have implemented a custom computer vision model using Azure AI Vision and deployed it to production. You want to monitor the model's performance and detect any potential issues or degradation over time. Which of the following approaches would be most effective for this purpose?
A
Periodically retrain the model with new data.
B
Monitor the model's input data distribution and detect any changes.
C
Set up alerts for high error rates or performance degradation.
D
Manually review the model's predictions periodically.