This project presents Machine Learning supervised algorithms that can predict the solar radiation levels based on the related features that could be helpful in predicting it. Moreover, the aim of this project was for people with sensitive skin that are most affected by Solar Radiation to help them avoid the exposure to excessive radiation and hence reduce the risk of getting a skin cancer.
The DataSet contains measurements of 4 months in a row (32,686 row) that is specified in date and time. It contains 7 features: Date, Time, Wind direction, Pressure, Wind speed, humidity and Temperature. The target parameter that is to be predicted is: Solar Radiation.