# Economic Growth in Developed and Developing Countries

Empirical machine learning project analyzing macroeconomic drivers of GDP growth across developed
and developing countries.

## Summary

This study uses World Bank macroeconomic indicators and Human Development Index data to compare
the drivers of economic growth across country development groups. It applies unsupervised learning
to classify countries and Random Forest regression to compare feature importance across groups.

## Methods

- K-means clustering for development-level grouping.
- Random Forest regression for GDP growth modeling.
- Feature importance analysis across macroeconomic indicators.
- Comparative analysis between developed and developing economies.

## Files

- `Economic Growth in Developed and Developing Countries.ipynb`: code and analysis notebook.
- `Economic Growth in Developed and Developing Countries.docx`: written methodology and findings.

## Portfolio Framing

This project demonstrates applied economic research, machine learning on macroeconomic panel data,
and communication of model-driven findings in a collaborative academic setting.