PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #233
PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #233: Real Exam Question with Answer & Explanation
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Question
You developed a custom model by using Vertex AI to predict your application's user churn rate. You are using Vertex AI Model Monitoring for skew detection. The training data stored in BigQuery contains two sets of features - demographic and behavioral. You later discover that two separate models trained on each set perform better than the original model. You need to configure a new model monitoring pipeline that splits traffic among the two models. You want to use the same prediction-sampling-rate and monitoring-frequency for each model. You also want to minimize management effort. What should you do?
Options
- AKeep the training dataset as is. Deploy the models to two separate endpoints, and submit two
- BKeep the training dataset as is. Deploy both models to the same endpoint and submit a Vertex AI
- CSeparate the training dataset into two tables based on demographic and behavioral features.
- DSeparate the training dataset into two tables based on demographic and behavioral features.
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