Covid-19 Future Forecasting Using Supervised Machine Learning Models

Abstract

AI (ML) based estimating instruments have demonstrated their importance to expect in perioperative results to improve the dynamic on the future course of activities. The Machine Learning(ML) models have for some time been utilized in numerous application spaces which required the ID and prioritization of unfavorable variables for a danger. A few expectation strategies are by and large famously used to deal with estimating issues. The spread of COVID-19 in the entire world has put the humankind in danger. The assets of probably the biggest economies are worried because of the enormous infectivity and contagiousness of this illness. 

Three sorts of expectations are made by every one of the models, for example, the quantity of recently tainted cases, the quantity of passing, and the quantity of recuperations But in the can't foresee the precise outcome for the patients. To defeat the issue, Proposed strategy utilizing the Exponential Smoothing (ES) algorithm, which anticipate the quantity of COVID-19 cases in next 30 days ahead and impact of preventive estimates like social privacy and lockdown on the spread of COVID-19