Traffic Accident Prediction Dashboard

This project uses real-world collision data from the City of Toronto to analyze and predict traffic accident patterns. It features an interactive dashboard that allows users to filter accidents by day and month, visualize impact types and top accident locations, and predict the type of collision impact using a trained machine learning model. Built using Python, scikit-learn, and Streamlit, the project demonstrates practical applications of data analysis, machine learning, and web deployment in a public safety context.