You are an AI engineer that works 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…

Question

Options

• AUse Vertex AI's prebuilt containers for prediction. Deploy the container on Cloud Run to generate
• BUse Vertex AI's prebuilt containers for prediction. Deploy the model on Google Kubernetes Engine
• CDeploy the model to a Vertex AI endpoint, and configure the model for batch prediction. Schedule
• DDeploy the model to a Vertex AI endpoint, and configure the model for online prediction. Schedule

• A
  4% (1)
• B
  4% (1)
• C
  84% (21)
• D
  8% (2)

Explanation

Deploying the model to a Vertex AI endpoint allows you to use Vertex AI's managed infrastructure, minimizing maintenance effort. Batch prediction is ideal for this use case, as the churn predictions are required weekly, not in real-time. It is cost-efficient and straightforward to schedule batch jobs to generate predictions for the entire customer dataset at regular intervals. Scheduling the batch prediction weekly aligns perfectly with the customer retention team's plan to act on predictions weekly.

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