🗂️ 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 In Progress |
• Automobiles & Vehicles • Finance • Marketing • Natural Language Processing • Regression |
Baseline: • Multiple Linear Regression Emsemble Trees • Random Forest • XGBoost |
|
Detecting Fake News In Progress |
• Social • Natural Language Processing |
Baseline: • Logistic Regression • SVM • Naive Bayes Deep Learning: • LSTM • BERT |
|
Screening for Chronic Kidney Disease Optimization |
• Medical | Baseline: • Logistic Regression Emsemble Trees • Random Forest • XGBoost |