Topic 1 Question 360
A manufacturing company produces 100 types of steel rods. The rod types have varying material grades and dimensions. The company has sales data for the steel rods for the past 50 years.
A data scientist needs to build a machine learning (ML) model to predict future sales of the steel rods.
Which solution will meet this requirement in the MOST operationally efficient way?
Use the Amazon SageMaker DeepAR forecasting algorithm to build a single model for all the products.
Use the Amazon SageMaker DeepAR forecasting algorithm to build separate models for each product.
Use Amazon SageMaker Autopilot to build a single model for all the products.
Use Amazon SageMaker Autopilot to build separate models for each product.
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コメント(2)
- 正解だと思う選択肢: A
This approach leverages the strengths of DeepAR to provide accurate and efficient sales predictions for the company's diverse product range.
👍 1MultiCloudIronMan2024/10/30 C; for operationally efficient A makes sense but requires operational work https://www.amazonaws.cn/en/sagemaker/autopilot/
👍 1spinatram2024/11/02
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