Predicting Air Quality in India Using Machine Learning Models

India's poor air quality is responsible for many health concerns, with chronic exposure to fine particulate matter (PM) leading to various health issues. Recently, the pollution levels in India have undergone various changes in the status of pollutants present in the air. Our paper aims to provide a comprehensive analysis of these issues highlighting the severe implications of poor air quality on public health in India and try to predict future health concerns due to poor air quality. In our work we have taken three machine learning modelslinear regression, decision tree regression, and K-Nearest Neighbour into the consideration to train our model. We have evaluated the models by using “R-squared score” and “mean square error”, to determine which was the best suitable model in predicting the Air quality with better accuracy. Our work contribute to ongoing efforts to improve the air quality forecasts model (AQI) and create effective solutions for a healthier India.