Data-Driven Retail Sales Forecasting Through Machine Learning Approaches

Abstract: This project investigates the efficacy of advanced Machine Learning models, including ensemble methods and deep learning architectures, in enhancing sales forecasting accuracy. By comparing their performance against classical time-series models across various datasets, we aim to demonstrate their superior ability to capture relationships and external influences, providing businesses with more reliable predictive tools for strategic planning and operational optimization.

Keywords: Machine Learning, Deep Learning, Sales Forecasting, Time-Series Models, Predictive Accuracy