Skip to main content
Back to Projects
ML & Data Science

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