ECOMERCRE SYSTEM INTERGRATE PREDICTING INCOME BASED ON DEEP LEARNING

Abstract

The thesis presents an e-commerce system integrated with income prediction capabilities for sellers using machine learning models. Its goal is to help sellers make better business decisions by analyzing sales data and forecasting future income. The system applies the XGBoost model for high prediction accuracy and is implemented and tested through a web-based interface.