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AWS Certified Machine Learning Engineer - Associate

  • Topic 1 Question 27

    A company uses a hybrid cloud environment. A model that is deployed on premises uses data in Amazon 53 to provide customers with a live conversational engine. The model is using sensitive data. An ML engineer needs to implement a solution to identify and remove the sensitive data. Which solution will meet these requirements with the LEAST operational overhead?

    • Deploy the model on Amazon SageMaker. Create a set of AWS Lambda functions to identify and remove the sensitive data.

    • Deploy the model on an Amazon Elastic Container Service (Amazon ECS) cluster that uses AWS Fargate. Create an AWS Batch job to identify and remove the sensitive data.

    • Use Amazon Macie to identify the sensitive data. Create a set of AWS Lambda functions to remove the sensitive data.

    • Use Amazon Comprehend to identify the sensitive data. Launch Amazon EC2 instances to remove the sensitive data.

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