Project Description
In this project, I worked with financial data from the Emerging Markets Information Service. I looked at financial indicators from Poland and Taiwan, and built supervised machine learning models (random forests & gradient boosting) that predict bankruptcy.
Overview
- Addressed imbalanced data using resampling techniques
- Evaluated models using classification metrics using precision and recall
- Improved bankruptcy models using random forests and gradient boosting
- Evaluated model generalizability using cross validation
- Tuned model hyperparameters using grid search
- Built prediction functions that use saved models
- Created Python modules to store prediction functions
Language & Tools
- Python (Pandas, Matplotlib, Seaborn, Scikit-learn)
Featured Notebooks
- To view featured notebooks, please send me an email at donald@donaldghazi.com