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Clustering Global Cities Based on Air Pollution Profiles
This project uses Unsupervised Learning (CLARA algorithm) to analyze air quality data from cities worldwide. It identifies distinct pollution profiles based on AQI, PM2.5, Ozone, CO, and NO2 values to group cities into different environmental categories.
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