Sales Forecasting Using Machine Learning Algorithm

Abstract

The goal of this project is to use machine learning to predict sales in retail stores. This study aims to establish model forecast accuracy by combining historical sales data with various factors such as advertising and seasonality, as well as external factors such as weather or social conditions._x000D_ Many machines learning algorithms, including more advanced models such as regression, decision trees, and neural networks, will be evaluated for their ability to accurately predict sales. To ensure the model, the data will be divided into training, validation, and testing._x000D_ Performance evaluation is based on measurements such as mean error (MAE) and root mean square error (RMSE). The most effective models will be selected and used to predict future sales to optimize inventory management and help make good sales decisions.