Pytorch

Demo | Demo (Streamlit) | GitHub

This is a nested logit discrete choice model implemented in PyTorch and deployed as a Streamlit app (containerized with Docker). The public ModeCanada dataset is used to model travel mode choice across train, car, bus, air using a two-level nest structure (Land vs. Air) where Land = {train, car, bus} and Air = {air}. Heterogeneous effects introduced via income and urban features. The project is framed as a hypothetical travel-agency e-ticketing case study, where train recall is prioritized to reduce missed public transport demand signals.