DATASET: [ Ссылка ]
project description:
The Air Quality Index (AQI) prediction system utilizes machine learning techniques to accurately forecast air quality. By leveraging numerical data and weather forecasts, the system builds regression and classification models to predict AQI values for different locations. Various evaluation metrics are employed to assess the performance of the models. The system incorporates data preprocessing, feature extraction, and model training processes. It merges regression and classification models to provide comprehensive air quality predictions. The system also includes performance evaluation and error analysis to identify areas for improvement. The final output displays the predicted AQI score and air quality classification. The system is deployed using Flask server and utilizes tools like HTML, JavaScript, and CSS for a user-friendly interface.
