Monitoring and Predicting Subway Passenger Demand in São Paulo City Using Machine Learning

This Omdena Local Chapter Challenge runs for 5 weeks and is a unique experience to try and grow your skills in a collaborative and safe environment with a diverse mix of people from all over the world. 

You will work on solving a local problem, initiated by São Paulo, Brazil Chapter.

The problem

The São Paulo city subway system comprises 6 lines with 91 stations. Every day on average more than 4 million people are transported. Although the system is under continuous update with new lines and stations being constructed, the passenger demand is still higher than transportation capacity in critical times every day. Only recently in the last years, the data for passenger demand has been opened to public access. There is no open monitoring system, dashboards, or predictive models to help the people and community decision-makers to understand the evolution and forecast the passenger demand for better urban planning.

The goals

With a duration of 5-weeks, this project aims to: 

• Data Collection and Preprocessing. 
• Exploratory Data Analysis 
• Data Visualization.
• Model Development and Training. 
• Web App Development.

Why join? The uniqueness of Omdena Local Chapter Challenges

Omdena Local Chapter Challenges are not a competition or hackathon but a real-world project that will grow your experience to a new level.

A unique learning experience with the potential to make an impact through the outcome of the project. You will go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join the global and collaborative community of Omdena with tons of benefits to accelerate your career.

Read more on how Omdena´s Local Chapters work