Abstract:-Coronavirus disease (COVID-19) is an inflammation disease from a new virus. Thedisease causes respiratory ailment (like influenza) with manifestations, forexample, cold, cough and fever, and in progressively serious cases, the problemin breathing. COVID-2019 has been perceived as a worldwide pandemic and a fewexaminations are being led utilizing different numerical models to anticipatethe likely advancement of this pestilence. These numerical models dependent ondifferent factors and investigations are dependent upon potential inclination.Here, we presented a model that could be useful to predict the spread ofCOVID-2019. We have performed linear regression, Multilayer perceptron andVector auto regression method for desire on the COVID-19 Kaggle data toanticipate the epidemiological example of the ailment and pace of COVID-2019cases in India; anticipated the potential patterns of COVID-19 effects in Indiadependent on data gathered from Kaggle. With the common data about confirmed,death and recovered cases across India for over the time length helps inanticipating and estimating the not so distant future. For extra assessment orfuture perspective, case definition and data combination must be kept uppersistently.
Keywords:COVID-19, exponentialsmoothing method, future forecasting, Adjusted R2 score, supervised machinelearning