Amazon AIF-C01 Practice Test - Questions Answers, Page 12

Which technique involves training AI models on labeled datasets to adapt the models to specific industry terminology and requirements?

HOTSPOT

A company is using a generative AI model to develop a digital assistant. The model's responses occasionally include undesirable and potentially harmful content. Select the correct Amazon Bedrock filter policy from the following list for each mitigation action. Each filter policy should be selected one time. (Select FOUR.)

* Content filters

* Contextual grounding check

* Denied topics

* Word filters

A manufacturing company wants to create product descriptions in multiple languages.

Which AWS service will automate this task?

A company trained an ML model on Amazon SageMaker to predict customer credit risk. The model shows 90% recall on training data and 40% recall on unseen testing data.

Which conclusion can the company draw from these results?

A company deployed a model to production. After 4 months, the model inference quality degraded. The company wants to receive a notification if the model inference quality degrades. The company also wants to ensure that the problem does not happen again.

Which solution will meet these requirements?

Why does overfilting occur in ML models?

A company wants to develop an Al application to help its employees check open customer claims, identify details for a specific claim, and access documents for a claim. Which solution meets these requirements?

A company is developing an ML application. The application must automatically group similar customers and products based on their characteristics.

Which ML strategy should the company use to meet these requirements?

HOTSPOT

A company wants to create an application to summarize meetings by using meeting audio recordings.

Select and order the correct steps from the following list to create the application. Each step should be selected one time or not at all. (Select and order THREE.)

* Convert meeting audio recordings to meeting text files by using Amazon Polly.

* Convert meeting audio recordings to meeting text files by using Amazon Transcribe.

* Store meeting audio recordings in an Amazon S3 bucket.

* Store meeting audio recordings in an Amazon Elastic Block Store (Amazon EBS) volume.

* Summarize meeting text files by using Amazon Bedrock.

* Summarize meeting text files by using Amazon Lex.