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Answer: Compare the mean average precision across the models using the Continuous Evaluation feature.
The correct answer is D. In the context of Google Cloud AI Platform, using the Continuous Evaluation feature is the most suitable approach for monitoring the performance of model versions over time. Continuous Evaluation allows you to compare performance metrics such as mean average precision (mAP) across different versions of your models, providing a robust mechanism for tracking and ensuring their ongoing accuracy and reliability.
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You have deployed multiple versions of an image classification model on Google Cloud AI Platform. These models are designed to identify different categories of images based on provided data. You want to continuously monitor the performance of each version of the model over time to ensure that they remain accurate and reliable. How should you perform this comparison?
A
Compare the loss performance for each model on a held-out dataset.
B
Compare the loss performance for each model on the validation data.
C
Compare the receiver operating characteristic (ROC) curve for each model using the What-If Tool.
D
Compare the mean average precision across the models using the Continuous Evaluation feature.