Predicting U.S. metro status using structural cost-of-living shares and machine learning.

Predict county-level electric vehicle (EV) adoption in the US using machine learning. This project uses time-series EV registration data and advanced feature engineering to train a Random Forest forecasting model, delivering 3-year local growth projections.

Interactive map exploring affordability across counties based on income and cost of living.