Building Time Series Prognostic Models to Analyze the Spread of COVID-19 Pandemic
Abstract
The COVID-19 was officially confirmed as a pandemic by World Health Organization (WHO). It is an infectious disease that has been spreading swiftly across the globe, creating unprecedented lockdowns. This virus spreads among humans through small droplets from the nose or mouth of an infected person. In this 21st century with most advanced technology available, we are not able to control it. In this paper, we will study how the Time Series based Machine Learning (ML) techniques are useful for analyzing and predicting the Confirmed cases, Recovered cases and Deaths caused by COVID-19. We analyze the spread of COVID-19 and try to forecast the possible cases in the coming days using the datasets from John Hopkins University. We implement different Regression techniques, Time series forecasting technique like Auto ARIMA, Facebook Prophet Model to analyze on the rise and extent of the virus.