Exam AWS Certified Machine Learning - Specialty topic 1 question 369 discussion

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

Question #: 369
Topic #: 1

[All AWS Certified Machine Learning - Specialty Questions]

A clothing company is experimenting with different colors and materials for its products. The company stores the entire sales history of all its products in Amazon S3. The company is using custom-built exponential smoothing (ETS) models to forecast demand for its current products. The company needs to forecast the demand for a new product variation that the company will launch soon.

Which solution will meet these requirements?

A. Train a custom ETS model.
B. Train an Amazon SageMaker DeepAR model.
C. Train an Amazon SageMaker К-means clustering model.
D. Train a custom XGBoost model.

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Suggested Answer: B 🗳️

by italiancloud2025 at Feb. 18, 2025, 5:38 p.m.

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italiancloud2025

2 months, 1 week ago

Selected Answer: B

A. No, porque un modelo ETS personalizado requiere historial del nuevo producto que no existe. B. Sí, porque DeepAR en SageMaker usa series relacionadas para predecir la demanda, incluso para nuevos productos. C. No, porque K-means es para agrupar datos, no para hacer predicciones de series temporales. D. No, porque XGBoost no está optimizado para pronósticos de series temporales en este caso.

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Exam AWS Certified Machine Learning - Specialty topic 1 question 369 discussion

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italiancloud2025

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