Abstract
: COVID-19 has proliferated over the earth, exposing mankind at risk. The assets of the
world's most powerful economies are at stake due to the disease's high infectivity and
contagiousness. The capacity of machine learning algorithms can estimate the amount of future
COVID-19 cases, which is now considered a possible threat to civilization. Five conventional
measuring models, notably LR, LASSO, SVM, ES, and LSTM, were utilised in this work to examine
COVID-19's undermining variables. Each model contains three sorts of expectations: the number
of newly contaminated cases, the number of passings, and the number of recoveries. However,
it is hard to anticipate the patients' real outcomes. To address the issue, a suggested approach
based on long transient memory (LSTM) forecasts the number of COVID-19 cases in the next 10
days as well as the impact of preventative measures such as social isolation and lockdown on
COVID-19 spread.