This project utilizes machine learning algorithms such as Random Forest and Support Vector Machines (SVM) to predict air pollution levels. The dataset includes environmental parameters like pollutant levels, weather conditions, and geographic data. The system can be used to forecast pollution levels in real-time and guide governmental and environmental agencies in pollution control.
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