AI-102 Implement generative AI solutions Practice Question
You are using Azure AI Document Intelligence to extract data from invoices. The invoices have varying layouts, and you need to build a custom model that can handle multiple document formats. Which type of model should you train?
⚠ Common exam trap
A common mix-up: candidates confuse custom template models (which require fixed layouts) with custom neural models (which handle varying layouts), leading them to select the template model due to familiarity with older OCR approaches.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Custom neural model
Custom neural models are designed to learn from diverse layouts without requiring manual labeling of field positions, making them ideal for invoices with varying formats. They use deep learning to understand document structure and extract fields accurately even when layouts differ significantly. This is the recommended approach for handling multiple invoice formats in Azure AI Document Intelligence.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Custom neural model
Why this is correct
Neural models handle varied layouts and learn from a variety of document structures.
- ✗
Custom template model
Why it's wrong here
Template models require consistent layouts.
- ✗
Prebuilt invoice model
Why it's wrong here
Prebuilt models are for fixed layouts only.
- ✗
Custom composed model
Why it's wrong here
Composed models combine multiple custom models but neural is more robust for varied layouts.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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