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…

Question

Options

• AUse the Amazon SageMaker DeepAR forecasting algorithm to build a single model for all the
• BUse the Amazon SageMaker DeepAR forecasting algorithm to build separate models for each
• CUse Amazon SageMaker Autopilot to build a single model for all the products.
• DUse Amazon SageMaker Autopilot to build separate models for each product.

• A
  78% (25)
• B
  6% (2)
• C
  13% (4)
• D
  3% (1)

Explanation

Amazon SageMaker DeepAR is a time series forecasting algorithm that is specifically designed to handle multiple time series data, such as sales data for different products, by training a single model across all related time series. This allows the model to share information across products and learn patterns more efficiently, which improves prediction accuracy and operational efficiency. Building a single model for all the products is more efficient than building separate models for each product, as it reduces the complexity and computation required. Separate models for each product using DeepAR would result in inefficiencies because training individual models for each product would require more computational resources and be less scalable. Using Autopilot is not the best solutions in this case because DeepAR is more specifically designed for time series forecasting tasks, making it more suitable for predicting future sales than the more general-purpose Autopilot.

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