Paper Contents
Abstract
The Placement Prediction Project aims to develop a machine learning-based system that predicts the likelihood of a student securing campus placement based on academic and non-academic parameters. By analyzing historical placement data, the model identifies key factors influencing placement success, such as academic performance, technical skills, soft skills, internships, and extracurricular activities. The system utilizes classification algorithms such as Logistic Regression, Decision Trees, and Random Forest to generate predictions and assess model accuracy. The goal is to provide students and institutions with actionable insights to improve employability outcomes. This project not only facilitates data-driven decision-making but also helps students understand and improve the key areas that impact their placement prospects.
Copyright
Copyright © 2025 Prof.Vashali warake . This is an open access article distributed under the Creative Commons Attribution License.
