Google Cloud Professional Machine Learning Engineer — Question 43

As the lead ML Engineer for your company, you are responsible for building ML models to digitize scanned customer forms. You have developed a TensorFlow model that converts the scanned images into text and stores them in Cloud Storage. You need to use your ML model on the aggregated data collected at the end of each day with minimal manual intervention. What should you do?

Answer options

• A. Use the batch prediction functionality of AI Platform.
• B. Create a serving pipeline in Compute Engine for prediction.
• C. Use Cloud Functions for prediction each time a new data point is ingested.
• D. Deploy the model on AI Platform and create a version of it for online inference.

Correct answer: A

Explanation

The correct answer is A because the batch prediction functionality of AI Platform allows you to process large sets of data at once, which aligns with your need for minimal manual intervention. Option B is not suitable as a serving pipeline in Compute Engine may require more management and does not specifically address batch processing. Option C involves unnecessary triggering for each new data point, and D focuses on online inference, which is not ideal for aggregated daily data.