Predicting air quality data by supervised learning algorithm

A machine learning code that utilizes Support Vector Machines (SVM) to predict air quality levels based on input features such as PM2.5, NO2, and SO2. The code aims to provide accurate air quality predictions, which can be valuable for monitoring and managing environmental conditions