Educational Recommendation System

This project develops an Education Recommendation System [ERS] using machine learning and Python tohelp students choose suitable career paths based on their academic performance and extracurricularinvolvement. The system utilizes a dataset containing student data, including subject scores, extracurricularactivities, and career aspirations. After preprocessing the data, various machine learning models such as KNearest Neighbours, Random Forest, and Support Vector Machines are trained to predict career aspirations.The best-performing model is selected and serialized for deployment. An interactive web application builtwith Flask allows users to input their academic and extracurricular information, receiving personalizedcareer recommendations based on their profiles. This project provides an accessible and efficient tool toguide students in making informed career decisions, highlighting how academic achievements andextracurricular activities influence potential career paths.