Exam AWS Certified Machine Learning - Specialty All Questions

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Exam AWS Certified Machine Learning - Specialty topic 1 question 127 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty

Question #: 127
Topic #: 1

[All AWS Certified Machine Learning - Specialty Questions]

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?

A. Create a workforce with AWS Identity and Access Management (IAM). Build a labeling tool on Amazon EC2 Queue images for labeling by using Amazon Simple Queue Service (Amazon SQS). Write the labeling instructions.
B. Create an Amazon Mechanical Turk workforce and manifest file. Create a labeling job by using the built-in image classification task type in Amazon SageMaker Ground Truth. Write the labeling instructions.
C. Create a private workforce and manifest file. Create a labeling job by using the built-in bounding box task type in Amazon SageMaker Ground Truth. Write the labeling instructions.
D. Create a workforce with Amazon Cognito. Build a labeling web application with AWS Amplify. Build a labeling workflow backend using AWS Lambda. Write the labeling instructions.

Show Suggested Answer

Suggested Answer: C 🗳️

by [deleted] at Feb. 6, 2021, 12:55 a.m.

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Highly Voted 2 years, 9 months ago

I would answer C, because of 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

upvoted 17 times

CharlesChiang

2 years, 8 months ago

Agree C

upvoted 3 times

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astonm13

2 years, 8 months ago

Yes it is C

upvoted 1 times

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cnethers

2 years, 9 months ago

agree C

upvoted 2 times

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benson2021

Highly Voted 2 years, 7 months ago

Answer is C. The question mentions that "to detect *areas* of concern on patients' CT scans", that can be achieved by bounding box instead of image classification. bounding box: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-bounding-box.html image classification: https://docs.aws.amazon.com/sagemaker/latest/dg/sms-image-classification.html

upvoted 8 times

ZSun

1 year, 2 months ago

The concern here is not about "object detection" or "image classification". it is about using "ground truth" and "private workforce"

upvoted 1 times

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jopaca1216

Most Recent 9 months, 2 weeks ago

The principal key is that Mechanical Turk workforce does not ensure privacy of the CT Scans, and Ground Truth does.

upvoted 3 times

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AjoseO

1 year, 4 months ago

Selected Answer: C

This option would allow the medical imaging company to create a private workforce, which can ensure that only authorized users have access to the scans, and to use Amazon SageMaker Ground Truth to create a labeling job, which would simplify the labeling pipeline process.

upvoted 3 times

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Shailendraa

1 year, 9 months ago

12-sep exam

upvoted 1 times

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ovokpus

2 years ago

Selected Answer: C

C - GroundTruth and privacy concerns

upvoted 2 times

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