정답:

Explanation:
Azure Text Analytics client library
The completed sentence is:
To develop an application that analyzes text by using Azure Language in Foundry Tools, use the Azure Text Analytics client library package.
Azure Language text analysis features include sentiment analysis, key phrase extraction, named entity recognition, language detection, and other text analytics capabilities. These are accessed by using the Azure Text Analytics client library.
The highlighted Azure Speech SDK option is incorrect because it is used for speech workloads, such as speech recognition and speech synthesis, not text analysis.

정답:

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.

정답: A  🗳️

정답:

Explanation:

Statement 1: Human-in-the-loop practices provide accountability for AI-generated decisions. = Yes Microsoft responsible AI guidance recommends keeping a human in the loop, maintaining human oversight, and ensuring humans have a role in decisions based on model output.
Statement 2: Deploying an AI system to a production environment eliminates the need for ongoing monitoring. = No Microsoft guidance states that after deployment, an AI-powered product or feature requires ongoing monitoring and improvement.
Statement 3: Disclosing the team that designed and deployed an AI system provides accountability for the system's output. = Yes Accountability in responsible AI means people and organizations remain responsible for AI systems and their effects. Identifying the people or team responsible for designing and deploying the system supports accountability and governance.