Prediction of Pollen Levels Using Machine Learning Techniques

This study explores the use of machine learning techniques for the prediction of pollen levels. The aim of the research is to develop an accurate model that can forecast pollen levels and help individuals with allergies to manage their symptoms. The study utilizes data from various sources, including pollen counts and applies machine learning algorithms. The results indicate that these techniques can provide accurate predictions of pollen levels, which can be used to support individuals with allergies and inform public health policies.