Weather Forecasting using Machine Learning and Markov Chains

This research aims to apply Machine Learning and Markov Chains in a novel way, and weather prediction is taken as a case. Through the use of historical weather data, precise Machine Learning models are created for each country, and the developed model provides a cutting-edge method for very accurate, real-time weather predictions. In addition to forecasting weather, the system also provides transition probabilities between different weather states. This system, which is easy to use and emphasizes accuracy and dependability, is a great resource for decision-making in areas such as transportation, agriculture, and emergency preparedness. Finally, this research addresses the drawbacks of conventional weather forecasting, making a substantial contribution to well-informed planning and the welfare of society.