Time-Series Retail Sales Forecasting
Global-pool ensemble for daily retail sales
PythonScikit-learnPandasARIMAstatsmodels
Overview
End-to-end forecasting pipeline (validation → EDA → features → baselines → ML → ensemble → report) on a year of daily retail sales for a small business client. Implements the global-pool approach from Montero-Manso & Hyndman (2021).
24% RMSE improvement over seasonal-naive baseline
Tech Stack
PythonScikit-learnPandasARIMAstatsmodels