Olympics Data Analysis Web App Lication and Prediction Using Machine Learning

The Olympics is a major international sporting events which has two aspects of competition namely summer and winter in which thousands of competitors from all over the globe compete in a variety of events. Olympics are more than just a four-stroke multi-sport world championship. It is a lens which gives us an understanding of global history, including shifting geopolitical power dynamics, women's empowerment, and the evolution of society's values. The Olympic Games had been come to be regarded as world’s leading sports competition, with more than 200 nations participating in it respectively. The total number of events in the Olympics is 46 but 2020 33 events took place. And there are winners in every event. Accordingly, various data are generated. The main goal is to shed light on major patterns in Olympic history. The NOC depends on where most athletes participate, the medal-winning probability, and the characteristics of the athletes (e.g., gender and physical size). Modules that will be implemented are Pandas for analyzing the data, NumPy for array processing, Matplotlib for mathematical extension, the Seaborn and Plotly libraries for plotting, and Random Forest regression for prediction