A GUI-Based Study of Weather Prediction Using Machine Learning Algorithms

The current climate is changing dramatically, making it more difficult and less accurate to anticipate the weather using traditional approaches. Improved and trustworthy weather forecast techniques are needed to get beyond these obstacles. Machine learning has tremendous influence in the modern-day world. Deep Learning and machine learning-based forecast systems can predict general weather patterns as well as numerical weather prediction models while using only a fraction of the computing power the models require. These models are developed in order to forecast weather variables such as solar radiation, temperature, and wind speed one to 24 h in advance. We have used supervised machine learning algorithms to predict the weather condition depending upon some parameters like temperature, humidity, precipitation, and wind speed. We have pre-processed the datasets and then after cross-validation, selected the most appropriate algorithm to predict the weather. We also developed a user interface to display the predicted results. The codes and website are available at https://github.com/98rupak/weather_project .