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NEW QUESTION # 88
What should you use to identify similar faces in a set of images?
Answer: A
Explanation:
To identify similar faces across different images using Azure, the Azure AI Face service is the most suitable choice. This service leverages AI algorithms to detect, recognize, and analyze human faces, including features like face grouping based on visual similarity.
Reference:
https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/how-to/find-similar-faces
NEW QUESTION # 89
You are developing an application that summarizes customer comments by using Azure Language in Foundry Tools.
You need to install the Azure Language SDK.
Which Python package should you install?
Answer: D
Explanation:
To summarize comments using Azure Language in Foundry Tools, you should install the azure- ai-textanalytics Python package.
Reference:
https://learn.microsoft.com/en-us/azure/foundry/how-to/develop/sdk-overview
NEW QUESTION # 90
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
The correct answer is natural language processing . In this scenario, a user communicates with a chatbot using ordinary human language, such as asking, "Will it rain today?" The chatbot must interpret the meaning and intent of the user ' s text, process the request, and formulate a natural-language response containing the relevant weather information. These are characteristic natural language processing (NLP) functions.
The current AI-901 study guide explicitly includes text analysis among the common AI workloads candidates must identify, and it also covers techniques for processing and interpreting human language. Microsoft documentation on conversational language understanding explains that conversational systems interpret user utterances to determine the user ' s intent and extract relevant information before the application performs an appropriate action.
Although the weather information itself may originate from a forecasting system, the scenario being tested centers on the chatbot interaction -understanding a natural-language question and responding conversationally. Therefore, prediction and forecasting is not the best classification of the complete interaction. Computer vision is also incorrect because no images or visual information are being analyzed.
NEW QUESTION # 91
You are developing a web app that processes invoices to calculate expenses.
You need to extract structured fields, including nested values, from the invoices by using a defined schema.
What should you use?
Answer: C
Explanation:
The requirement is to extract structured fields, including nested values, from invoices by using a defined schema . In Azure Content Understanding, an analyzer is the processing unit that defines how content is analyzed, what information is extracted, and how the output is structured, including JSON fields.
Microsoft's Content Understanding document solutions documentation states that Content Understanding uses customizable analyzers to extract essential information, fields, and relationships from documents and forms.
Microsoft's quickstart also shows invoice processing with the prebuilt-invoice analyzer to extract structured data from an invoice document.
Why the other options are incorrect:
A). transcription workflow in Azure Speech is for converting audio to text, not invoice field extraction.
B). OCR-only document processing can extract text but does not meet the requirement for structured fields and nested values by schema.
D). Azure AI Search is for indexing and querying content, not defining invoice extraction schemas.
Therefore, the correct answer is C. an analyzer in Azure Content Understanding in Foundry Tools .
NEW QUESTION # 92
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Statement 1: In the new Microsoft Foundry portal, you must fine-tune a model before you can deploy the model. = No Fine-tuning is optional. Microsoft's Foundry model deployment documentation describes deploying Foundry Models directly from the model catalog for inference. It does not require fine-tuning first.
Statement 2: In the new Microsoft Foundry portal, you can test a model from the model catalog only after you deploy the model. = No Microsoft documentation states that some Foundry Tools are available to try via the model catalog without a project , and Foundry playgrounds are used for prototyping and validation before production.
Therefore, the statement using "only after you deploy" is too restrictive.
Statement 3: In the new Microsoft Foundry portal, you can deploy a model from the model catalog only after retraining the model. = No Retraining/fine-tuning is not required before deployment. Microsoft states that after you deploy a Foundry Model, you can interact with it in the Foundry Playground and use it from code, and the deployment workflow starts by selecting a model from the model catalog and choosing Deploy .
NEW QUESTION # 93
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