Campus Placement using Machine Learning: An Extensive Review and Comparative Study of Machine Learning Methods

Unemployment has been one of the most socio-economic issues. Many countries are facing challenges related to both open unemployment where individuals are actively seeking jobs and are unable to find them. In the present era of education and workforce dynamics is characterized by diversity, demanding many innovative ideas, tools and strategies for talent matching and resource allocation methods. The traditional methods of placement process are often reliant on manual evaluations and are quite inadequate in meeting the needs for individuals and organizations. This study highlights the reasons behind the growing need for Machine Learning based placement assessment. It ensures efficient talent matching, reducing costs, and saving time. The paper highlights the advantages of remote and flexible assessments, displaying how technology can replace the old methods of hiring.