PLACEMENT PREDICTION AND ANALYSIS USING MACHINE LEARNING

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