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NEW QUESTION # 98
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
Named Entity Recognition (NER) is used to extract dates, quantities, and locations from text.
Named Entity Recognition identifies and categorizes entities in text, such as people, organizations, locations, dates, times, quantities, currencies, and other structured information.
The other options are incorrect:
Key phrase extraction identifies important phrases or main topics.
Language detection identifies the language of the text.
Sentiment Analysis identifies positive, negative, neutral, or mixed sentiment.
NEW QUESTION # 99
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: Azure Content Understanding in Foundry Tools can analyze only PDF documents. = No Azure Content Understanding is not limited to PDF documents. It can analyze different content types, including documents, forms, images, audio, and video.
Statement 2: Azure Content Understanding in Foundry Tools results are returned in the JSON format. = Yes Azure Content Understanding returns structured analysis output in JSON format.
Statement 3: Azure Content Understanding in Foundry Tools can extract structured fields from documents and forms. = Yes Azure Content Understanding can extract structured fields from documents and forms by using analyzers and schemas.
NEW QUESTION # 100
Which type of compute resource should you use to attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning?
Answer: A
Explanation:
To attach an existing Azure Kubernetes Service (AKS) cluster to Azure Machine Learning, you should use the "Attached Compute" or "Kubernetes Compute Target". This allows you to leverage your existing AKS cluster as a compute resource for your machine learning tasks within Azure Machine Learning. You can achieve this using the Azure CLI v2, Python SDK v2, or Machine Learning Studio UI.
1. Kubernetes Compute Target:
Azure Machine Learning treats your AKS cluster as a compute target, allowing you to specify it as the location for running your training jobs or deploying models.
2. Attached Compute:
This refers to the ability to connect existing compute resources, like your AKS cluster, to your Azure Machine Learning workspace.
Reference:
https://learn.microsoft.com/en-us/azure/machine-learning/how-to-attach-kubernetes-to-workspace
NEW QUESTION # 101
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation:
The correct selection is AIProjectClient . In the Microsoft Foundry SDK, AIProjectClient serves as the primary project-level client for accessing and managing resources associated with a Foundry project.
Microsoft documentation specifically exposes operation groups through this client for deployments , agents , and indexes , which directly matches the requirements stated in the question.
For example, the SDK exposes deployments operations for working with models deployed to the project, agents operations for creating and managing agents, and indexes operations for accessing project search indexes. Microsoft also describes the Azure AI Projects client library as a unified Foundry SDK component that connects applications to project resources through a single project endpoint.
ChatCompletionsClient is focused primarily on model inference and chat-completion operations rather than comprehensive project-resource management. FoundryLocalManager is associated with local Foundry capabilities, while ModelCatalogClient would relate to model discovery/catalog functionality rather than deployments, agents, and indexes collectively.
Therefore, the class required for this scenario is AIProjectClient .
NEW QUESTION # 102
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:
NEW QUESTION # 103
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