Analyze the spread of coronavirus in the world to predict new cases under machine learning techniques

Coronavirus is a worldwide pandemic disease. At the same time, it is making unexpected changes in different countries of the World, with new variants in each region due to their autonomous climates. That is why the coronavirus is mutating, and there is a massive contagion that causes death. Consequently, it is necessary to analyze and identify where the new cases occurred and where is the possible area of attack of the new variant of covid 19. It is also necessary to know the characteristics and the stage of infection of patients with covid 19. This research method is based on a branch of artificial intelligence, machine learning; the idea is to use artificial intelligence techniques to analyze and predict new coronavirus cases, using classification models, decision trees, and the Bernoulli model. The case study was used to input a real-time database with a systematic record of covid-19 from 2020 to the present. Accordingly, the data and properties for implementing the model and training were defined to make the corresponding predictions of new cases of covid 19. Finally, as a final result, predictions of the number of new cases and total deaths of covid 19 in the World were made. Finally, this research aims to analyze the data on the spread of Covid-19 in the World to predict new cases and help society prevent new variants of Covid 19 by using artificial intelligence to provide various related solutions.