Answer: Time series data

## 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.

Author: Ritesh Yadav