A Review on Placement Prediction and Analysis Using Machine Learning

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Authors: Pranay Rapartiwar, Sanket Agade, Ashwini Mirge, Janvi Wakde, Sumit Sanjay Muddalkar
Cited by: 0
References: 7

Abstract

The rate at which the students are placed in jobs are considered an essential aspect of measuring the efficacy of a particular institution in imparting proper training to its students, which leads to placement in jobs. Many a learner takes due interest in studying the placement rate when deciding which institution to choose as a place to educate themselves at the collegiate level in colleges or universities. Enhancing the placement opportunities of the students in jobs is considered a major goal of almost all academic institutions, and this review paper is a study dedicated to laying a foundation in the aspect of campus placement prediction using machine learning as a predictive tool. By delving into the subject of machine learning as a predictive tool, this paper serves as a directional path that stimulates future research after pointing out the existing shortcomes in this type of prediction in raising awareness in a basic way regarding the accuracy of the efficiency of a machine learning-based campus placement prediction system.

Fields of Study & Subjects

Online Learning and Analytics Data Mining and Machine Learning Applications AI and HR Technologies

Publication details

Journal / source
International Journal of Scientific Research in Science and Technology
Volume
13
Issue
1
Pages
416–421
Publication date
28 February 2026
Language
EN