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Answer: Create a Vertex AI Model Monitoring job to track the model's performance with production data, and trigger retraining when specific metrics drop below predefined thresholds.
Option A is the correct answer because it directly addresses the requirement to automatically retrain the model when performance deteriorates using Vertex AI Model Monitoring, which is specifically designed for this purpose. It continuously tracks model performance metrics on production data and can trigger retraining when thresholds are breached. Option C is less suitable because it uses a static dataset, which doesn't capture real-time performance degradation in production. Option B relies on manual user feedback, which isn't automated. Option D focuses on bias detection and feature importance shifts rather than direct performance monitoring, which is the primary concern stated in the question. The community discussion shows 67% support for A, with comments emphasizing that only A properly addresses performance monitoring and automated retraining.
Author: LeetQuiz Editorial Team
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You are managing a production Vertex AI model and want to automatically trigger retraining when model performance degrades. What should you do?
A
Create a Vertex AI Model Monitoring job to track the model's performance with production data, and trigger retraining when specific metrics drop below predefined thresholds.
B
Collect feedback from end users, and retrain the model based on their assessment of its performance.
C
Configure a scheduled job to evaluate the model's performance on a static dataset, and retrain the model if the performance drops below predefined thresholds.
D
Use Vertex Explainable AI to analyze feature attributions and identify potential biases in the model. Retrain when significant shifts in feature importance or biases are detected.
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