DMP: Machine Learning Based Classification of Urban Air Quality in Gijón, Spain

The dataset used in this project contains hourly air quality and weather measurements collected in the city of Gijón, Spain, during 2013. It includes variables such as pollutant concentrations (PM2.5, NO₂, CO, O₃, SO₂) and environmental factors like temperature, humidity, wind speed, and pressure. The data is provided in CSV format, where each row represents measurements at a specific time and location. For this project, the dataset was cleaned and preprocessed by handling missing values, translating column names, and selecting relevant features. A new target variable, Air_Quality_Class, was created to categorize air quality into Good, Moderate, and Poor. The dataset was then split into training, validation, and test sets, and used to train machine learning models for classification.