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Exam AI-102 All Questions

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Exam AI-102 topic 4 question 25 discussion

Actual exam question from Microsoft's AI-102
Question #: 25
Topic #: 4
[All AI-102 Questions]

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You have an Azure subscription.

You plan to build a solution that will analyze scanned documents and export relevant fields to a database.

You need to recommend which Azure AI service to deploy for the following types of documents:

• Internal expenditure request authorization forms
• Supplier invoices

The solution must minimize development effort.

What should you recommend for each document type? To answer, select the appropriate options in the answer area.

NOTE: Each correct selection is worth one point.

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a8da4af
Highly Voted 6 months, 1 week ago
Correct answer, verified with ChatGPT Internal expenditure request authorization forms These forms are likely to be custom and specific to your organization, so a pre-built model might not accurately extract the fields you need. Recommendation: Azure AI Document Intelligence custom model Supplier invoices Invoices are common and well-understood document types that Azure already provides pre-built models for. Recommendation: Azure AI Document Intelligence pre-built model
upvoted 6 times
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syupwsh
Most Recent 2 months, 2 weeks ago
Internal expenditure request authorization forms - An Azure AI Document Intelligence custom model is CORRECT because internal expenditure request authorization forms typically have unique structures and specific fields that are not covered by pre-built models. By creating and training a custom model, you can accurately extract the relevant fields from these specialized forms. This approach minimizes development effort by leveraging Azure AI Document Intelligence’s capabilities to train models with your specific dataset, ensuring precise data extraction tailored to your organizational needs. Supplier invoices - An Azure AI Document Intelligence pre-built model is CORRECT because it offers specialized models for common document types like supplier invoices. Using a pre-built model minimizes development effort by providing out-of-the-box capabilities to extract relevant fields such as invoice numbers, dates, and amounts without the need for custom training. This ensures efficient and accurate data extraction tailored to typical invoice structures.
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