You have deployed an ML model to a Vertex AI endpoint and set up a Vertex AI Model Monitoring job. To continuously evaluate the model by monitoring for feature attribution drift, what steps should you take?

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Set up alerts using Cloud Logging, and use the Vertex AI console to review feature attributions.

33.3%

Set up alerts using Cloud Logging, and use Looker Studio to create a dashboard that visualizes feature attribution drift. Review the dashboard periodically.

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Enable request-response logging for the Vertex AI endpoint, and set up alerts using Pub/Sub. Create a Cloud Run function to run TensorFlow Data Validation on your dataset.

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Enable request-response logging for the Vertex AI endpoint, and set up alerts using Cloud Logging. Review the feature attributions in the Google Cloud console when an alert is received.

66.7%

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You have deployed an ML model to a Vertex AI endpoint and set up a Vertex AI Model Monitoring job. To continuously evaluate the model by monitoring for feature attribution drift, what steps should you take?