Google Professional Machine Learning Engineer
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Your team is developing a cutting-edge application for a multinational bank designed to serve millions of customers worldwide. The application includes a forecasting model that predicts individual customers' account balances three days in advance with high accuracy. The team aims to leverage these predictions to introduce a proactive feature that alerts users via notifications when their account balance is predicted to fall below a critical threshold of $25, helping them avoid potential overdraft fees. Given the bank's emphasis on scalability, cost-efficiency, and personalized user experience, which of the following solutions BEST meets these requirements? Choose the two most appropriate options.
A
Implement a dedicated Pub/Sub topic for each user to manage notifications. Deploy the application on Google App Engine's standard environment, which processes the predictions and sends notifications when a user's balance is predicted to drop below $25.
B
Utilize Firebase to construct a notification system. Register each user with a unique identifier in Firebase Cloud Messaging (FCM), configuring it to send notifications based on the average predicted balance of all users falling below $25.
C
Create a Pub/Sub topic for each user to handle notifications. Deploy a Cloud Function that triggers notifications when the model predicts a user's balance will drop below $25.
D
Build a notification system on Firebase, registering each user with a unique ID in Firebase Cloud Messaging (FCM). Configure FCM to send personalized notifications when the model predicts an individual's balance will drop below $25.
E
Combine the use of Firebase for user registration and notifications with Cloud Functions for processing predictions. Register each user in FCM and use a Cloud Function to analyze predictions and trigger FCM notifications for balances predicted below $25.