Air Quality and Pollution Assessment Using Machine Learning Techniques

Air quality has become a critical environmental and public health concern due to rapid urbanization, industrial activities, and increased vehicular emissions. Accurate assessment and prediction of air pollution levels are essential for informed policy-making and early warning systems. This study investigates the application of machine learning techniques for analyzing air quality data and forecasting pollutant concentrations. This dataset contains environmental and air quality data collected to study the factors affecting air pollution levels in different regions. The dataset includes features related to environmental conditions, pollution indices, and contextual environmental factors. It supports air quality analysis and predictive modeling to better understand the impacts of pollution on human health and the environment.