This project applies Linear Regression to predict air quality based on weather and environmental factors. By collecting data such as temperature, humidity, and particulate matter concentrations, the model predicts air quality levels in the near future. The project includes data cleaning, feature selection, and evaluating the model’s performance with real-world data.
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