Seismic damage prediction for residential buildings in Mexico City

Data science and machine learning applied to observations following the 2017 Puebla earthquake.

This project applies data science and machine learning to building damage observations collected following the 2017 Puebla earthquake in Mexico City.

The research examines how building characteristics, location, and seismic demand can support damage prediction.