Professional-Machine-Learning-Engineer Exam Dumps | You recently deployed a model to a Vertex Al endpoint Your data drifts frequently so you have enabled

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Question 74

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Question 74/139

You recently deployed a model to a Vertex Al endpoint Your data drifts frequently so you have enabled request-response logging and created a Vertex Al Model Monitoring job. You have observed that your model is receiving higher traffic than expected. You need to reduce the model monitoring cost while continuing to quickly detect drift. What should you do?

A. Replace the monitoring job with a DataFlow pipeline that uses TensorFlow Data Validation (TFDV).

B. Replace the monitoring job with a custom SQL scnpt to calculate statistics on the features and predictions in BigQuery.

C. Decrease the sample_rate parameter in the Randomsampleconfig of the monitoring job.

D. Increase the monitor_interval parameter in the scheduieconfig of the monitoring job.

Correct Answer: C

According to the official exam guide1, one of the skills assessed in the exam is to "configure and optimize model monitoring jobs". The Vertex AI Model Monitoring documentation states that "to reduce the cost of model monitoring, you can configure the sample rate of the requests that are logged and analyzed by model monitoring". Therefore, decreasing the sample_rate parameter in the Randomsampleconfig of the monitoring job would reduce the model monitoring cost while continuing to quickly detect drift. The other options are not relevant or optimal for this scenario. References:
* Preparing for Google Cloud Certification: Machine Learning Engineer Professional Certificate
* Professional ML Engineer Exam Guide
* Google Professional Machine Learning Certification Exam 2023
* Latest Google Professional Machine Learning Engineer Actual Free Exam Questions
* [Vertex AI Model Monitoring]

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