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NEW QUESTION # 101
You are developing an application that uses the Azure Language SDK and a Microsoft Foundry resource.
You need to return a list of important topics from unstructured text.
Which Python method should you use?
Answer: C
Explanation:
To return a list of important topics from unstructured text using the Azure Language Python SDK within a Microsoft Foundry resource, you should use the extract_key_phrases method.
Depending on whether you are running synchronous or asynchronous operations for large batches of documents, choose one of the following methods from the TextAnalyticsClient:
client.extract_key_phrases(documents)
Used for immediate, synchronous processing of text data. It returns results in real time and is ideal for smaller or interactive application workloads.client.begin_extract_key_phrases(documents) Used for asynchronous (batch) processing. It returns a long-running operation poller, which is highly recommended when analyzing large volumes of unstructured text or multiple documents simultaneously.
Reference:
https://notes.kodekloud.com/docs/AI-102-Microsoft-Certified-Azure-AI-Engineer-Associate/Analyzing-Text/Working-with-Azure-AI-Language-Services/page
NEW QUESTION # 102
You have 100 instructional videos that do NOT contain any audio. Each instructional video has a script.
You need to generate a narration audio file for each video based on the script.
Which type of workload should you use?
Answer: B
NEW QUESTION # 103
You are designing a system that will generate insurance quotes automatically.
Match the Microsoft responsible AI principles to the appropriate requirements.
To answer, drag the appropriate principle from the column on the left to its requirement on the right. Each principle may be used once, more than once, or not at all.
NOTE: Each correct match is worth one point.
Answer:
Explanation:
Explanation:
Requirement
Principle
The decision-making process must be recorded so that staff can identify the reasoning behind a particular quote.
Transparency
A customer ' s personal information must be visible only to staff who are involved in the decision-making process.
Privacy and security
The system must be accessible to customers who use screen readers or other assistive technology.
Inclusiveness
Microsoft ' s Responsible AI framework defines six core principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, and accountability.
The first requirement maps to Transparency because personnel must be able to understand and review how the AI system arrived at an insurance quote. Transparency concerns making AI behavior, capabilities, limitations, and decision processes understandable. Recording the decision-making process provides the traceability required to explain a particular result.
The second requirement maps to Privacy and security. Restricting customer information to authorized staff directly implements least-privilege access and protects confidential personal data from unauthorized disclosure. Microsoft specifically associates this principle with respecting data boundaries and safeguarding information handled by AI systems.
The third requirement maps to Inclusiveness. AI systems should accommodate the full range of people they serve, including individuals who rely on assistive technologies. Support for screen readers and accessibility technologies ensures that users with disabilities are not excluded from interacting with the system. Microsoft explicitly connects inclusive AI design with accessibility considerations for people with disabilities.
NEW QUESTION # 104
Capturing text from images is an example of which type of Al capability?
Answer: D
Explanation:
Capturing or reading text from images is optical character recognition (OCR) . OCR is used to detect and extract printed or handwritten text from images, scanned documents, and other visual content.
NEW QUESTION # 105
What should you use to compare benchmark metrics of different AI models?
Answer: D
Explanation:
To compare benchmark metrics across Azure AI models, navigate to the Azure AI Foundry portal, explore the model catalog, and use the benchmarking tools to assess model performance. You can then compare these metrics to choose the most suitable model for your needs.
Reference:
https://learn.microsoft.com/en-us/azure/ai-foundry/how-to/benchmark-model-in-catalog
NEW QUESTION # 106
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