Crime Forecasting to Enhance Safety Measures in São Paulo Using Machine Learning

This Omdena Local Chapter Challenge runs for 7 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

Predicting future crimes can provide valuable insights for decision-making and the planning of public safety policies. With a reliable prediction model and an interactive web app, we can empower users to visualize crime predictions by region in an intuitive format, facilitating the understanding and utilization of this information to enhance public safety.

The goals

• Develop a machine learning model capable of predicting the number of crimes by region and crime category for future periods, using a historical dataset containing information about crimes.
• Create an interactive web app that allows users to visualize crime predictions on a map, with the ability to filter by region, crime category, and specific dates.
• Facilitate the understanding and utilization of future crime predictions, making the information accessible and useful to the general public.

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