Analysis and Prediction of COVID-19 Spread in India

Novel Coronavirus, also known as COVID-19 has spread globally which is sparked in Wuhan, the capital city of Hubei in China. It is a big problem for the world’s health organization as the number of affected cases as well as deaths increases in each country. Several Machine Learning models are designed to predict and forecast the COVID-19 outbreak. In this paper, we are designed to understand the current scenario of coronavirus, and predicting and forecasting the total number of confirmed cases of novel COVID-19 in India using linear regression, polynomial regression, and support vector machine regression models. The decision-making process of an organization depends on the data analysis and it is presenting with interactive visual representation. It is not possible to predict without having necessary information from the past and the present. Trends over time tell us where we were and where we can go with our model. The model is predicting the number of confirmed cases from 30th May 2021 to 15th June 2021on the data available from 22 January 2020 to 29 May 2021. Forecasting the future of confirmed cases can help health organizations to plan medical facilities. Moreover, the time series forecasting technique is being engaged to forecast the overall total of confirmed cases in the upcoming.