This project uses Gradient Boosting Machines (GBM) for predicting air pollution levels based on environmental data. By analyzing historical data of pollutants and weather patterns, the model is able to predict future pollution levels with high accuracy. The project helps authorities in cities and regions prepare for air quality-related health concerns.
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