Admission Recommender System

Abstract

The goal of this project is to design an Admission Recommender System specific to Master’s programs and based on the prediction of candidates’ performances based on key indicators such as GRE scores and CGPA. The system then applies the machine learning algorithm by training the system on precedent admission records to discern patterns and correlations between applicants’ academic profile data and their admission decisions. Thus, the Admission Recommender System helps the applicants and the admissions committees to make a proper selection, thereby providing the opportunity to improve the admissions process of the Master’s programs.