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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 362 discussion

A data scientist uses Amazon SageMaker to perform hyperparameter tuning for a prototype machine leaming (ML) model. The data scientist's domain knowledge suggests that the hyperparameter is highly sensitive to changes.

The optimal value, x, is in the 0.5 < x < 1.0 range. The data scientist's domain knowledge suggests that the optimal value is close to 1.0.

The data scientist needs to find the optimal hyperparameter value with a minimum number of runs and with a high degree of consistent tuning conditions.

Which hyperparameter scaling type should the data scientist use to meet these requirements?

  • A. Auto scaling
  • B. Linear scaling
  • C. Logarithmic scaling
  • D. Reverse logarithmic scaling
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Suggested Answer: D 🗳️

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MultiCloudIronMan
2 weeks, 1 day ago
Selected Answer: D
This approach allocates more search effort near the higher end of the range, ensuring that values closer to 1.0 are explored more thoroughly, thus meeting the need for a minimum number of runs while maintaining consistent tuning conditions
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