HR Employee Attrition Analysis & Prediction

Data Cleaning: Removed redundant features and addressed outliers with IQR clipping.

EDA: Visualized turnover drivers, highlighting higher attrition in younger employees (20s).

Imbalance Handling: Applied SMOTE for class imbalance.

Predictive Modeling: Developed and evaluated a Logistic Regression model to classify potential leavers and gain

insights into retention strategies.