Abstract:
In this century, educational institutes have stored a lot of student data which is increasing
constantly. This data contains various attributes like student grades, school, and
family-related features. It is needed to analyze those data to predict students’
performance for the development in the field of education. To evaluate this study, we
have applied Machine Learning Algorithms like Simple Linear Regression, Support
Vector Regression, Random Forest Regression. This research also aims to prove how
different factors and variables affect the predicted student's success rate.