Time series Covid 19 Predictions with Machine Learning Models

Abstract

The year 2020 began with the outbreak of covid-19 Pandemic, it originated in China and very quickly spread to all the other parts of the world. The deadly virus badly affected the health and economy of Mankind. This work aims to build Machine learning models to predict the spread of Covid -19. The up to date Time series data set of Covid 19 is used in the analytics. Three prediction models namely Regression, SVM and FBProphet are implemented. The results obtained from these models are investigated. FBProphet gives promising results as compared to the other models. The trend and seasonality components of FBProphet are shown to be very useful in the analysis of Time Series Data.