🗂️ Project Portfolio

Welcome to my data science and machine learning project portfolio! This repo showcases a collection of hands-on analytics, machine learning, and NLP projects tackling real-world challenges in finance, healthcare, and AI.

Each project entry below links to code, step-by-step notebooks, and experiment results. Categories and methods (like Baseline, Ensemble Trees, Deep Learning) are broken down for clarity — so you can jump right into the action that interests you.

Check out the table below for quick access to project descriptions and the core approaches behind each one. Click any project title to dive in.

Project	Topic	ML Algorithm	Hightlights
Predicting Credit Card Customer Churn: A Data-Driven Approach to Retention Strategy	• Finance • Business • Banking • Classification	Baseline:    • Logistic Regression Emsemble Trees    • Random Forest    • XGBoost	- 🚀 99% ROC-AUC (XGBoost) - 🔍 Explainable AI: SHAP & feature importance - 📈 +10% recall via SMOTE - 🏆 Actionable churn drivers for business
Used Car Price Prediction: Predictive Modeling with Real-World Data	• Automobiles & Vehicles • Finance • Marketing • Regression • Feature Engineering • Model Interpretability	Baseline:    • Multiple Linear Regression Ensemble Trees    • Random Forest    • XGBoost    • LightGBM    • CatBoost	- 🏆 RMSE ↓ 8.5% vs. baseline - 🔎 Top price drivers identified (hp, mileage, year) - 💡 Explainable ML: SHAP & feature importances - 🛠️ Automated, modular ML pipeline