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Exam AWS Certified Machine Learning - Specialty All Questions

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Exam AWS Certified Machine Learning - Specialty topic 1 question 365 discussion

Exam question from Amazon's AWS Certified Machine Learning - Specialty
Question #: 365
Topic #: 1
[All AWS Certified Machine Learning - Specialty Questions]

A data scientist needs to develop a model to detect fraud. The data scientist has less data for fraudulent transactions than for legitimate transactions.

The data scientist needs to check for bias in the model before finalizing the model. The data scientist needs to develop the model quickly.

Which solution will meet these requirements with the LEAST operational overhead?

  • A. Process and reduce bias by using the synthetic minority oversampling technique (SMOTE) in Amazon EMR. Use Amazon SageMaker Studio Classic to develop the model. Use Amazon Augmented Al (Amazon A2I) to check the model for bias before finalizing the model.
  • B. Process and reduce bias by using the synthetic minority oversampling technique (SMOTE) in Amazon EMR. Use Amazon SageMaker Clarify to develop the model. Use Amazon Augmented AI (Amazon A2I) to check the model for bias before finalizing the model.
  • C. Process and reduce bias by using the synthetic minority oversampling technique (SMOTE) in Amazon SageMaker Studio. Use Amazon SageMaker JumpStart to develop the model. Use Amazon SageMaker Clarify to check the model for bias before finalizing the model.
  • D. Process and reduce bias by using an Amazon SageMaker Studio notebook. Use Amazon SageMaker JumpStart to develop the model. Use Amazon SageMaker Model Monitor to check the model for bias before finalizing the model.
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Suggested Answer: C 🗳️
by MultiCloudIronMan at Oct. 30, 2024, 10:42 p.m.
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MultiCloudIronMan
2 weeks, 1 day ago
Selected Answer: C
This approach leverages the integrated tools within Amazon SageMaker to streamline the process, reduce operational overhead, and ensure the model is both effective and unbiased.
upvoted 1 times
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