ENGINEERING COLLEGE SEAT PREDICTION USING MACHINE LEARNING

Abstract

The rapid advancements in technology and data analytics have enabled predictive modelling to play a crucial role in various domains, including education. Engineering seat prediction is a data-driven approach that leverages historical admission trends, student performance metrics, reservation policies, and other relevant factors to estimate a student's chances of securing a seat in an engineering college. This predictive system aims to assist students in making informed decisions about their preferred institutions and courses, thereby reducing uncertainty and anxiety during the admission process.