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最新的 AWS Certified AI AI1-C01 免費考試真題:

1. Which functionality does Amazon SageMaker Clarify provide?

A) Documents critical details about ML models
B) Integrates a Retrieval Augmented Generation (RAG) workflow
C) Monitors the quality of ML models in production
D) Identifies potential bias during data preparation

2. A medical company deployed a disease detection model on Amazon Bedrock. To comply with privacy policies, the company wants to prevent the model from including personal patient information in its responses. The company also wants to receive notification when policy violations occur.
Which solution meets these requirements?

A) Use Guardrails for Amazon Bedrock to filter content. Set up Amazon CloudWatch alarms fornotification of policy violations.
B) Use Amazon Macie to scan the model's output for sensitive data and set up alerts for potential violations.
C) Implement Amazon SageMaker Model Monitor to detect data drift and receive alerts when model quality degrades.
D) Configure AWS CloudTrail to monitor the model's responses and create alerts for any detected personal information.

3. A company has documents that are missing some words because of a database error. The company wants to build an ML model that can suggest potential words to fill in the missing text.
Which type of model meets this requirement?

A) BERT-based models
B) Topic modeling
C) Clustering models
D) Prescriptive ML models

4. A company makes forecasts each quarter to decide how to optimize operations to meet expected demand. The company uses ML models to make these forecasts.
An AI practitioner is writing a report about the trained ML models to provide transparency and explainability to company stakeholders.
What should the AI practitioner include in the report to meet the transparency and explainability requirements?

A) Model convergence tables
B) Code for model training
C) Partial dependence plots (PDPs)
D) Sample data for training

5. A company is developing a new model to predict the prices of specific items. The model performed well on the training dataset. When the company deployed the model to production, the model's performance decreased significantly.
What should the company do to mitigate this problem?

A) Add hyperparameters to the model.
B) Increase the model training time.
C) Increase the volume of data that is used in training.
D) Reduce the volume of data that is used in training.

問題與答案：