This project aims to analyze student performance using Support Vector Machines (SVM) and provide insights through a mobile-friendly web application. By examining various factors such as demographic details, study habits, parental involvement, and extracurricular activities, the project seeks to predict student performance measured by their GPA.
The purpose of this project is to leverage machine learning to enhance educational outcomes by identifying key factors that influence student performance. By providing detailed analysis and predictions, educators can tailor interventions to support student success.
This project is a collaborative effort, and we would like to thank all contributors and supporters, especially those who provided the data and technical guidance.