Air Quality Index Prediction

Falling back past few years rapid progress in Air pollution has become a life-threatening concern many nations throughout the world due to human activity, industrialisation, and urbanisation.. As result of these activities, sulphur oxides, carbon dioxide (CO2), nitrogen monoxide (CO), chlorofluorocarbons (CFC), lead, mercury, other pollutants be emitted into atmosphere. Simultaneously, estimating quality air is tough undertaking because evolution, variability, also unreasonable unpredictability over particle region time. In this project we compare two Algorithms machine learning predicting Index Quality its predominant. Support vector (SVM) exists as prominent method beneficial forecasting pollutant plus levels index (AQI), Random Forest Regression another. We'll working with data from India's Open Government Data Platform. This website displays readings around India, including Sulphur Dioxide (SO2), Nitrogen (NO2), Particulate Matter (PM) are examples contaminants (PM10 PM2.5), Carbon Monoxide others. The output predict using different algorithms comparison models various error metrics.