PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #147
PROFESSIONAL-MACHINE-LEARNING-ENGINEER Question #147: Real Exam Question with Answer & Explanation
Sign in or unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER to reveal the answer and full explanation for question #147. The question stem and answer options stay visible for context.
Question
You work for an online publisher that delivers news articles to over 50 million readers. You have built an AI model that recommends content for the company's weekly newsletter. A recommendation is considered successful if the article is opened within two days of the newsletter's published date and the user remains on the page for at least one minute. All the information needed to compute the success metric is available in BigQuery and is updated hourly. The model is trained on eight weeks of data, on average its performance degrades below the acceptable baseline after five weeks, and training time is 12 hours. You want to ensure that the model's performance is above the acceptable baseline while minimizing cost. How should you monitor the model to determine when retraining is necessary?
Options
- AUse Vertex AI Model Monitoring to detect skew of the input features with a sample rate of 100%
- BSchedule a cron job in Cloud Tasks to retrain the model every week before the newsletter is
- CSchedule a weekly query in BigQuery to compute the success metric.
- DSchedule a daily Dataflow job in Cloud Composer to compute the success metric.
Unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER to see the answer
You've previewed enough free PROFESSIONAL-MACHINE-LEARNING-ENGINEER questions. Unlock PROFESSIONAL-MACHINE-LEARNING-ENGINEER for full answers, explanations, the timed quiz mode, progress tracking, and the master PDF. Question stem and options stay visible so you can still see what's on the exam.