Main Article Content
Abstract
Employee training programs play a vital role in skill development and workforce productivity. However, evaluating their effectiveness remains a challenge. This study presents a data-driven approach using machine learning techniques, including regression analysis and clustering, to assess training outcomes. A regression model predicts post-training performance, while clustering groups employees based on improvement levels. The system also incorporates sentiment analysis for feedback evaluation. Experimental results show over 90% accuracy in predicting training effectiveness. The developed model, integrated with an interactive dashboard, enables HR managers to make data-backed decisions. Future enhancements include AI-driven adaptive training recommendations.