About

This canvas implements a complete production-ready demand forecasting API system that trains a Gradient Boosting model on 3 years of real-world retail sales data, validates performance with time-series cross-validation and backtesting, and exposes two REST endpoints (/predict for demand forecasts with confidence intervals and /health for model metrics). The workflow engineers 29 features from raw sales data, generates predictions with 95% and 80% confidence intervals, visualizes model performance and data patterns, and includes comprehensive API validation, error handling, and deployment documentation.