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Free Microsoft AI-900 Exam Braindumps (page: 12)

Page 12 of 70
PDF with 273 Questions

Which Azure service can use the prebuilt receipt model in Azure AI Document Intelligence?

  1. Azure AI Services
  2. Azure Machine Learning
  3. Azure AI Vision
  4. Azure AI Custom Vision

Answer(s): A

Explanation:

Azure AI Services, Document Intelligence Document Intelligence receipt model
The Document Intelligence receipt model combines powerful Optical Character Recognition (OCR) capabilities with deep learning models to analyze and extract key information from sales receipts. Receipts can be of various formats and quality including printed and handwritten receipts.


Reference:

https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/concept-receipt



HOTSPOT (Drag and Drop is not supported)
Select the answer that correctly completes the sentence.
Hot Area:

  1. See Explanation section for answer.

Answer(s): A

Explanation:




Box: obtain approval based on their intended usage
As part of the Microsoft responsible AI principles, customers must       before they can use Azure OpenAI.
Microsoft legal resources, Limited access to Azure OpenAI Service Registration process
Azure OpenAI requires registration and is currently only available to approved enterprise customers and partners. Customers who wish to use Azure OpenAI are required to submit a registration form.
Customers must attest to any and all use cases for which they will use the service (the use cases from which customers may select will populate in the form after selection of the desired model(s) in Question 22 in the initial registration form). Customers who wish to add additional use cases after initial onboarding must submit the additional use cases using this form. The use of Azure OpenAI is limited to use cases that have been selected in a registration form. Microsoft may require customers to re-verify this information. Read more about example use cases and use cases to avoid here.


Reference:

https://learn.microsoft.com/en-us/legal/cognitive-services/openai/limited-access



What is an example of a Microsoft responsible AI principle?

  1. AI systems should protect the interests of developers.
  2. AI systems should be in the public domain.
  3. AI systems should be secure and respect privacy.
  4. AI systems should make personal details accessible.

Answer(s): C

Explanation:

Responsible AI principles
* Fairness: AI systems should treat all people fairly. Reliability and safety: AI systems should perform reliably and safely. Privacy and security: AI systems should be secure and respect privacy. Inclusiveness: AI systems should empower everyone and engage people.
Etc.


Reference:

https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/strategy/responsible-ai



What should you do to reduce the number of false positives produced by a machine learning classification model?

  1. Include test data in the training data.
  2. Increase the number of training iterations.
  3. Modify the threshold value in favor of false positives.
  4. Modify the threshold value in favor of false negatives.

Answer(s): D

Explanation:

If you have a classifier which calculates a real values score and then a threshold is applied to define what is classified as positive or negative. By changing this threshold you can decrease the number of false positives at the expense of increasing the number of false negatives.


Reference:

https://www.quora.com/Why-does-my-artificial-neural-network-predict-too-many-false-positives-FP



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