A comprehensive machine learning project demonstrating loan default prediction.
- 94% accuracy with optimized KNN model
- 95% accuracy with neural network approach
- SHAP analysis for model interpretability
- Bias detection and fairness evaluation
- Multiple ML algorithms comparison
- Python, Pandas, NumPy
- Scikit-learn, SHAP
- Matplotlib for visualization
- Jupyter Notebooks
- Successfully handled imbalanced dataset
- Comprehensive feature engineering
- Model explainability implementation
- Clone the repository
- Install requirements:
pip install -r requirements.txt - Run the Jupyter notebook
- Explore the analysis and results
This project demonstrates practical ML skills for financial services, including regulatory compliance considerations and responsible AI implementation.
Git workflow should be updated.