On Campus Student Recruitment Analysis using Machine Learning techniques

A nonprofit organization like college, works to assist all student needs and advance science, particularly in the academic sector. Hence, offering a high-quality placement aid service has emerged as a key indicator of a college’s overall quality. Nowadays, in this pandemic-affected world, the majority of IT organizations are hiring students online, which makes it difficult for the college and the company to shortlist the students based on the requirements of the companies for various tasks. Due to the large number of students at colleges, the recruitment process requires a lot of human labor. We, therefore, offer a novel method for assessing job applications in online recruitment systems by using several machine learning methods to address the issue. We attempt to put into practice an application in the form of a prototype system, whose functionality is displayed and accessed in a genuine recruitment scenario. It is possible to offer a system where a computer would examine both the company’s needs and the student’s performance to determine whether the student should be selected for an interview.The analysis of student recruitment is automated in this paper utilizing machine learning methods by comparing the scores of a test with the benchmark score of the company.