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In this paper, we propose a machine learning technics and SIR models(deterministic and stochastic cases) with numerical approximations to predictthe number of cases infected with the COVID-19, for both in few days and thefollowing three weeks. Like in [1] and based on the public data from [2], weestimate parameters and make predictions to help on how to find concreteactions to control the situation. Under optimistic estimation, the pandemic insome countries will end soon, while for most of the countries in the world, thehit of anti-pandemic will be no later than the beginning of May.

Comparative prediction of confirmed cases with COVID-19 pandemic by machine learning, deterministic and stochastic SIR models