Google Cloud Professional Machine Learning Engineer — Question 196

You work for a social media company. You want to create a no-code image classification model for an iOS mobile application to identify fashion accessories. You have a labeled dataset in Cloud Storage. You need to configure a training workflow that minimizes cost and serves predictions with the lowest possible latency. What should you do?

Answer options

• A. Train the model by using AutoML, and register the model in Vertex AI Model Registry. Configure your mobile application to send batch requests during prediction.
• B. Train the model by using AutoML Edge, and export it as a Core ML model. Configure your mobile application to use the .mlmodel file directly.
• C. Train the model by using AutoML Edge, and export the model as a TFLite model. Configure your mobile application to use the .tflite file directly.
• D. Train the model by using AutoML, and expose the model as a Vertex AI endpoint. Configure your mobile application to invoke the endpoint during prediction.

Correct answer: B

Explanation

The correct answer is B because AutoML Edge allows for efficient model training optimized for mobile devices, and exporting it as a Core ML model is ideal for iOS applications. The other options either involve unnecessary steps, such as batch requests or using TFLite, which is not as optimal for iOS compared to Core ML.