Optimizing-Employee-Productivity-An-Analysis-on-the-Impact-of-Mental-Health-on-Workplace-Performance

Conducted a comprehensive Exploratory Data Analysis (EDA) and statistical evaluation to investigate the impact of employee mental health on workplace productivity.

Utilized regression models to analyze relationships between mental health variables and work performance, and applied unsupervised learning techniques, including K-Means clustering, anomaly detection, and Principal Component Analysis (PCA), to uncover patterns and anomalies in the data.

Employed Python (Pandas, NumPy, Matplotlib, Seaborn) and advanced visualization tools to present insights clearly.

Developed actionable recommendations to help corporates improve work environments and boost employee productivity, integrating data-driven strategies for enhanced organizational effectiveness.