The project's objective is to assist prospective students in determining the university tier where they are most likely to secure admission. This will be achieved by analyzing historical admission and rejection data from various universities to provide predictions regarding the universities or tiers of universities where a student has a favorable probability of gaining admission.
Language: Python
Modules: SKLearn, Pandas
- Student Profile: This dataset, having 25 features, contains details about student profile like GRE score, research & work experience etc., and the university in which he/she got admission.
- World University Ranking: This dataset, with 21 features, contains world university ranking of universities with details like employer& academic reputation, student to faculty ratio etc. We’ll be using this dataset to find universities which are similar to each other to create the tiers of university.
A detailed explanation of the project, findings and results in a Presentation slide format available