AWS Certified Cloud Practitioner

Explanation

The correct answer is C. Time series data because:

1. Amazon SageMaker DeepAR is specifically designed for time series forecasting problems.
2. Time series data consists of observations collected at regular time intervals (daily, weekly, monthly, etc.), which is exactly what's needed for demand forecasting.
3. Demand prediction for retail products involves analyzing historical sales patterns over time to forecast future demand.
4. The other options are incorrect:
   • A. Text data: Used for natural language processing tasks, not forecasting
   • B. Image data: Used for computer vision tasks, not time-based predictions
   • D. Binary data: Typically used for classification problems, not sequential forecasting

DeepAR algorithm requires time series data as input, where each time series represents historical demand for a specific product, and it uses this sequential data to make probabilistic forecasts for future time periods.