Google Cloud Professional Machine Learning Engineer — Question 66

You need to build an ML model for a social media application to predict whether a user’s submitted profile photo meets the requirements. The application will inform the user if the picture meets the requirements. How should you build a model to ensure that the application does not falsely accept a non-compliant picture?

Answer options

• A. Use AutoML to optimize the model’s recall in order to minimize false negatives.
• B. Use AutoML to optimize the model’s F1 score in order to balance the accuracy of false positives and false negatives.
• C. Use Vertex AI Workbench user-managed notebooks to build a custom model that has three times as many examples of pictures that meet the profile photo requirements.
• D. Use Vertex AI Workbench user-managed notebooks to build a custom model that has three times as many examples of pictures that do not meet the profile photo requirements.

Correct answer: A

Explanation

The correct answer is A because optimizing for recall specifically focuses on reducing false negatives, which is crucial for ensuring non-compliant photos are not accepted. Options B, C, and D do not prioritize minimizing false negatives, with B focusing on balancing scores and C and D improperly adjusting the dataset without addressing the false acceptance issue.