nerdexam
Amazon

MLS-C01 · Question #137

A medical imaging company wants to train a computer vision model to detect areas of concern on patients' CT scans. The company has a large collection of unlabeled CT scans that are linked to each…

The correct answer is C. Create a private workforce and manifest file. The requirement that authorized users should only have access. These users will comprise the private workforce of AWS Ground Truth. See documentation: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-private.html

Machine Learning Implementation and Operations

Question

A medical imaging company wants to train a computer vision model to detect areas of concern on patients' CT scans. The company has a large collection of unlabeled CT scans that are linked to each patient and stored in an Amazon S3 bucket. The scans must be accessible to authorized users only. A machine learning engineer needs to build a labeling pipeline. Which set of steps should the engineer take to build the labeling pipeline with the LEAST effort?

Options

  • ACreate a workforce with AWS Identity and Access Management (IAM).
  • BCreate an Amazon Mechanical Turk workforce and manifest file.
  • CCreate a private workforce and manifest file.
  • DCreate a workforce with Amazon Cognito.

How the community answered

(28 responses)
  • A
    7% (2)
  • B
    14% (4)
  • C
    75% (21)
  • D
    4% (1)

Explanation

The requirement that authorized users should only have access. These users will comprise the private workforce of AWS Ground Truth. See documentation: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-workforce-private.html

Topics

#SageMaker Ground Truth#Data Labeling#Private Workforce#Data Security

Community Discussion

No community discussion yet for this question.

Full MLS-C01 Practice