Explanation:
Explanation:
Option A is the best choice for this Proof-of-Concept scenario:
Cloud Vision AutoML:
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NO.24 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?
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.
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