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Omdena

Local Chapter project

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

Data ScienceEDAData VisualizationMachine LearningPredictive Analytics
Start date
May 31, 2023
Finish date
July 8, 2023
Project status
completed
Monitoring and Predicting Subway Passenger Demand in São Paulo City Using Machine Learning

Challenge background

São Paulo city is the capital of the Brazilian state with the same name. It is the most populous city in Brazil and the fourth most populous in the world. São Paulo Metropole or the Great São Paulo Area joins 39 cities with around 27 million people and has different urban problems, including public transportation planning.

Project timeline

  1. 1

    Week 1

    Problem statement. Data collection, cleaning, and preprocessing. Creation of a common data source for the project.

  2. 2

    Week 2

    Exploratory data analysis, creation of dashboards, and generating insights.

  3. 3

    Week 3

    Development and training of forecast and machine learning models.

  4. 4

    Week 4

    Development of web application with dashboards and models created.

  5. 5

    Week 5

    Web app deployment. Project final discusions and next steps.

What you'll learn

Data collection, data cleaning and preprocessing, exploratory data analysis, dashboard creation and insights, development and model training, and web app development.

Get involved

What to expect from a Local Chapter project

First project

  • Welcomes beginners and experienced practitioners.
  • Focuses on education and collaborative delivery.
  • Produces open-source project work.

Benefits

  • Address a significant real-world problem with your skills.
  • Build your project portfolio.
  • Demonstrate your work to organizations and project partners.

Requirements

  • Working English communication.
  • A learning mindset.
  • Commitment to collaborative project work.

This challenge is hosted by

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