Crime Data Prediction using Machine Learning

Making our communities safer is the straightforward but impactful foundation of this dissertation. It focuses on developing a machine learning model that can assist in forecasting potential crime scenes and times, allowing us to take action before damage is done. This work urges us to reframe safety as care, support, and astute intervention before things go wrong, rather than as punishment after the fact. This study not only provides a new tool by fusing technology and empathy, but it also points to a new direction where data helps us understand people and public safety is a shared, compassionate responsibility.