This study focuses on a system that predicts if a student would be placed or not based on the student’s qualifications, historical data, and experience. This predictor uses a machine-learning algorithm to give the result.
The Placement Predictor is an innovation in recruitment system based on the cantidates skill set on various parameters like CGPA, level of problem solving skills, communication skills, teamwork skill, number of projects, cometitions and internships. It is aimed to develop an automation in placement prediction at college level which predicts the chances of an undergraduate student getting placed in an IT company and helps him/her profiling themselves before the recruitment process starts.
It involves the use of machine learning model of k-nearest neighbor algorithm as base model to classify students or users into appropriate clusters and the result would help them in pointing out weaknesses and gives a chance for improving their skillset. The results of the same is also compared with the results obtained from other models like linear regression, for optimal solution. With various data cleaning techniques using python libraries like Numpy, pandas, matplotlib, and machine learning techniques, this proposition would help both students as well as recruiters during placements and other recruitment activities. Run app.py to see the website.