Abstract
With the development of various industries, air pollution is also increasing day by day, and hence the air is getting harmful for living beings whether it be humans or animals. Some of the major factors in determining air pollution are Aerosol Optical Thickness/Depth (AOT/AOD), Ml, and M2. This paper proposes determining the most important factors in determining the PM2.5 level using feature selection methods and developing a model to predict the PM2.5 level using neural network regression on the Azure ML studio platform.