Visualization & Prediction of COVID-19 Future Outbreak by Using Machine Learning

Day by day, the accumulative incidence of COVID-19 is rapidly increasing. After spread Corona epidemic and death more than a million people around world countries, scientists researchers have tended to conduct research take advantage modern technologies learn machine help get rid Coronavirus (COVID-19) epidemic. To track predict disease Machine Learning (ML) can be deployed very effectively. ML techniques been anticipated in areas that need identify dangerous negative factors define their priorities. The significance proposed system find number infected with COVID19 using ML. Four standard models anticipate prediction, which are Neural Network (NN), Support Vector Machines (SVM), Bayesian (BN) Polynomial Regression (PR). data utilized test these content deaths, newly cases, recoveries next 20 days. Five measures parameters were used evaluate performance each model, namely root mean squared error (RMSE), (MAE), absolute (MSE), Explained Variance score r2 (R2 ). value auspicious mechanism for current scenario results showed NN outperformed other models, while available dataset SVM performs poorly all prediction. Reference our injuries will increase slightly coming Also, we give rise hope due low rate. For future perspective, case explanation amalgamation must kept up persistently.