Google Cloud Professional Data Engineer — Question 111

You work for a manufacturing company that sources up to 750 different components, each from a different supplier. You've collected a labeled dataset that has on average 1000 examples for each unique component. Your team wants to implement an app to help warehouse workers recognize incoming components based on a photo of the component. You want to implement the first working version of this app (as Proof-Of-Concept) within a few working days. What should you do?

Answer options

• A. Use Cloud Vision AutoML with the existing dataset.
• B. Use Cloud Vision AutoML, but reduce your dataset twice.
• C. Use Cloud Vision API by providing custom labels as recognition hints.
• D. Train your own image recognition model leveraging transfer learning techniques.

Correct answer: A

Explanation

The correct answer is A because using Cloud Vision AutoML with the existing dataset allows for quick setup and deployment, leveraging Google's pre-built capabilities for image recognition. Option B is less effective as reducing the dataset could hinder the model's performance. Option C involves using the API without training a custom model, which may not provide the specificity needed for recognizing components. Option D, while valid, would require more time and expertise to implement compared to using AutoML.