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Urban Crime Forecasting & Hotspot Detection
Data / ML2023

Urban Crime Forecasting & Hotspot Detection

ML pipeline over 1M+ Chicago crime records with XGBoost and geospatial visualization

About This Project

Developed a machine learning pipeline that processes over 1 million Chicago crime records to forecast crime patterns and identify hotspots. Used XGBoost for predictive modeling with extensive feature engineering, and created geospatial visualizations to help law enforcement agencies allocate resources more effectively.

Technologies Used

PythonXGBoostPandasGeospatial AnalysisData Visualization