Coronavirus is a quickly spreading viral sickness that contaminates people and the day to day existence of individuals, their wellbeing, and the economy of a nation are impacted because of this lethal viral illness. Many endeavors have been directed to track down a reasonable and quick method for recognizing contaminated patients in a beginning phase. The spread of COVID-19 in the entire world has seriously jeopardized the humankind. The assets of the absolute biggest economies are worried because of the huge infectivity and contagiousness of this sickness. The ability of Machine Learning models and Deep Learning models can be actually used to estimate the quantity of impending cases impacted by COVID-19 which is by and by viewed as a likely danger to humankind. Specifically, seven standard determining models, in particular LR, LASSO, SVM, NN, XGB Regressor, Random Forest Regressor have been utilized in this review to estimate the compromising elements of COVID-19. Three kinds of assumptions are made by all of the models, similar to the amount of as of late spoiled cases, the amount of passings, and the amount of recoveries.
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