Paper Key : IRJ************581
Author: Om Darkunde,Omkar Koli,Anuja Pawar,Vedika Bhuvad
Date Published: 20 Nov 2024
Abstract
The rapid evolution of todays job market challenges educational institutions to prepare students for successful employment. To address this, we introduce a Campus Placement Prediction System that leverages machine learning to forecast placement outcomes, enabling institutions to make data-driven decisions, identify at-risk students, and enhance employability support. By analyzing factors like academic performance, skills, internships, and extracurricular activities, the system provides actionable insights into key employability factors. Using algorithms such as logistic regression, decision trees, and random forests, it predicts outcomes with over 80% accuracy, with random forests performing best. The anonymized dataset, encompassing grades, skills, and experiences, was preprocessed for consistency, and critical predictors like academic scores, internships, and technical skills were identified through feature selection and correlation analysis. This system empowers institutions to optimize curricula, offer tailored support, and align student development with industry demands.
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