Metro-Flow This repository explores the application of machine learning and deep learning algorithms to uncover patterns in the flow and diffusion of passengers within a metro network. By analyzing transit data, we aim to provide insights into user behavior, network efficiency, and congestion dynamics.
https://colab.research.google.com/drive/1KuedZz5e9FefHqKOd7tw-z4RwyEdilA2?usp=sharing
The GIF shows the concurrence at each Chicago metro station during the year 2023. All the data comes from: https://data.cityofchicago.org/