Professional-Machine-Learning-Engineer Exam Dumps | You are an AI engineer working for a popular video streaming platform. You built a classification model

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Question 51

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Question 51/137

You are an AI engineer working for a popular video streaming platform. You built a classification model using PyTorch to predict customer churn. Each week, the customer retention team plans to contact customers identified as at-risk for churning with personalized offers. You want to deploy the model while minimizing maintenance effort. What should you do?

A. Use Vertex AI's prebuilt containers for prediction. Deploy the container on Cloud Run to generate online predictions.

B. Use Vertex AI's prebuilt containers for prediction. Deploy the model on Google Kubernetes Engine (GKE), and configure the model for batch prediction.

C. Deploy the model to a Vertex AI endpoint, and configure the model for batch prediction. Schedule the batch prediction to run weekly.

D. Deploy the model to a Vertex AI endpoint, and configure the model for online prediction. Schedule a job to query this endpoint weekly.

Correct Answer: C

Deploying the model on Vertex AI with a batch prediction configuration is ideal for weekly inference jobs since the retention team needs predictions once per week. Scheduling batch predictions minimizes computational costs, and Vertex AI's endpoint management simplifies infrastructure setup without needing additional maintenance. Using Vertex AI's prebuilt containers also provides a flexible deployment pipeline for any future model updates. Options A and D do not suit batch needs, and GKE (Option B) requires more manual maintenance.

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