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Exam Cloud Digital Leader topic 1 question 267 discussion

Actual exam question from Google's Cloud Digital Leader
Question #: 267
Topic #: 1
[All Cloud Digital Leader Questions]

A manufacturing organization has a large collection of images labeled as intact or defective parts. They want to use this data to build a simple solution to detect faulty parts on their production line. They have no data science expertise. Which solution should they use?

  • A. Pre-trained APIs
  • B. Document AI
  • C. AutoML
  • D. Discovery AI for Retail
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Suggested Answer: C 🗳️
by joshnort at Jan. 21, 2025, 9:16 p.m.

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joshnort
3 months, 1 week ago
Selected Answer: C
C. AutoML AutoML is a tool that allows organizations without data science expertise to build custom machine learning models. It can take labeled datasets, like the organization's collection of intact and defective part images, and train a model to automatically classify new images. AutoML Vision, in particular, is designed for image recognition tasks, making it ideal for detecting faulty parts based on labeled images.
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joshnort
3 months, 1 week ago
Why not the other options? A. Pre-trained APIs: Pre-trained APIs (e.g., Vision API) are great for general image recognition tasks but cannot be customized to a specific use case like detecting defective parts in a manufacturing setting. B. Document AI: Document AI is designed for processing and extracting data from documents (e.g., invoices, receipts). It is not applicable to image-based classification tasks. D. Discovery AI for Retail: Discovery AI is designed for e-commerce and retail applications, such as personalized recommendations and search, not for manufacturing or image classification. Conclusion: AutoML provides an accessible, no-code/low-code solution to train a custom image classification model that meets the organization's needs for detecting defective parts.
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