Student Placement Prediction System

Abstract

Every educational institution relies on campus placement to assist students in achieving their objectives. Machine learning classification can be used to retrieve associated data from huge student datasets. In this examination, a prescient model is fostered that can conjecture the positions for which students are eligible based on their academic and extracurricular achievements in the past. The model will also propose additional abilities that will be necessary for future recruitment, which will aid students in their preparation for placement. It also gives continuous trial results and discoveries, as well as execution estimations expected for model approval, aiding the accomplishment of the achievement of result based training at instructive foundations, which is agreed first concern in the current context.