Exam AI-102 topic 3 question 53 discussion

Actual exam question from Microsoft's AI-102

Question #: 53
Topic #: 3

DRAG DROP
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You are building a customer support chatbot.

You need to configure the bot to identify the following:

• Code names for internal product development
• Messages that include credit card numbers

The solution must minimize development effort.

Which Azure Cognitive Service for Language feature should you use for each requirement? To answer, drag the appropriate features to the correct requirements. Each feature may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.

NOTE: Each correct selection is worth one point.

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Suggested Answer:

by 973b658 at June 14, 2023, 9:41 a.m.

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zellck

Highly Voted 1 year, 11 months ago

1. Custom NER 2. PII detection https://learn.microsoft.com/en-us/azure/cognitive-services/language-service/custom-named-entity-recognition/overview Custom NER enables users to build custom AI models to extract domain-specific entities from unstructured text, such as contracts or financial documents. By creating a Custom NER project, developers can iteratively label data, train, evaluate, and improve model performance before making it available for consumption. The quality of the labeled data greatly impacts model performance. https://learn.microsoft.com/en-us/azure/cognitive-services/language-service/personally-identifiable-information/overview PII detection is one of the features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. The PII detection feature can identify, categorize, and redact sensitive information in unstructured text. For example: phone numbers, email addresses, and forms of identification.

upvoted 27 times

rdemontis

1 year, 7 months ago

thank you for your great contribution

upvoted 5 times

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syupwsh

Most Recent 4 months ago

Code names for internal product development --> Custom named entity recognition (NER) is CORRECT because it allows you to train the model to recognize specific entities, such as code names for internal product development, which are not covered by the pre-built NER models. This feature provides the flexibility to identify custom entities relevant to your specific use case, minimizing development effort. Messages that include credit card numbers --> Personally Identifiable Information (PII) detection is CORRECT because it is specifically designed to identify sensitive personal information such as credit card numbers, social security numbers, and other PII in text. This feature directly addresses the requirement to detect messages that include credit card numbers with minimal development effort.

upvoted 2 times

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