Public safety is a topic of great importance, and predicting crimes can be a valuable tool for resource allocation and strategic planning for law enforcement agencies. In this project, we aim to develop a machine learning model to predict the number of crimes by crime category, month/year and region inside of São Paulo State. Additionally, we will create an interactive web app to visualize crime predictions on a map, allowing users to explore the predictions for future dates.
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.
Onboarding; literature review; code availability; brainstorming; problem statement.
Data collection and preparation.
Exploratory data analysis.
Development of a predictive model.
Testing and validation.
Web app development.
Web app deployment; project review.