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Implementation of option pricing models using Numba that performs better. This entire project has utilized as little libraries as possible, even though certain models have their own Machine Learning Model with assessment and performance.
🚗 A dynamic pricing and insurance risk modeling system using Python, XGBoost, SHAP, and DVC. Predicts claim severity and probability, enabling risk-adjusted premium strategies with full reproducibility and CI/CD.
This repository documents a complete ML workflow to model Uber fares in Paris, from granular EDA and feature engineering to building and fine-tuning a stacking regressor on 10k real-world rides.