Engineered end-to-end data pipelines for 48,000+ property listings and developed rental price prediction models, improving R2 score from 83.27% to 85.89%.
Applied ensemble learning on real world property data using Random Forest, XGBoost, and LightGBM along with feature engineering and hyperparameter tuning to improve prediction accuracy.