MFE admission prediction — GPBoost model (AUC 0.723) on 12,800+ records, 29 programs, 930 LinkedIn profiles. Pure data-driven, no manual tuning.

Admission Prediction website in US elite colleges. This website uses a Machine Learning model trained using Linear Regression technique. Website takes score as input from users to predict the results based on previously trained Machine Learning model.

🎓 Graduate Admission Chances Prediction – A Machine Learning model that predicts the probability of a student getting admitted to a university based on GRE score, TOEFL score, CGPA, SOP, LOR, and research experience. Built with Regression models, Scikit-Learn, Pandas, and Python.

A web Portal Used for the Prediction of Admission Jobs in Engineering and Technology /Management/Pharmacy with respect to demographic locations.