Organizations face the ongoing challenge of effectively evaluating and predicting employee performance to enhance productivity and make informed HR decisions. Traditional performance assessment methods often lack objectivity and fail to capture complex patterns in employee behavior and performance metrics.
This project aims to carry out in-depth analysis of employee performance and create an Employee Performance Prediction system using the Multi-Layer Perceptron (MLP) Classifier based on the analysis that has been carried out. By leveraging advanced machine learning techniques, we strive to provide a more accurate and data-driven approach to performance evaluation. This system will enable organizations to identify high performers, anticipate potential performance issues, and adjust development programs, ultimately resulting in a more efficient and motivated workforce.