In this research paper, machine learning-based models are used for predicting the number of countries that have been affected by the COVID-19 virus and what was the situation of them. Then, the analysis is performed whether the “Lockdown” is the savior or not, and how India faced the whole problem. After that the prediction model for India was also prepared. These are the selected ones that are comprised in this paper. The COVID virus has spread globally, causing thousands of deaths and having an enormous impact on our health systems and economies. As soon as the Covid-19 pandemic was hit hard worldwide, lots of researchers were trying to figure out lot more things, among them when and from where did the virus make its an outbreak. The whole analysis part is based on the data science and machine learning algorithms and utterly dependent on the data collected from various trusted sources. In this paper, decision tree-based linear (DTBL) model and Random Forest Regression (RFR) models are applied to ensure the accuracy of the models. The Auto-Regressive Integrated Moving Average (ARIMA) and Prophet Algorithm are used for the prediction model. Preventive measures to reduce the spread of the COVID virus in respective zones are also suggested. We hope that this research work will help in the understanding and eradication of the threatening disease. This study can be applied by other countries for predicting COVID-19 cases at the state or national level. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Covid-19—Analysis and Prediction—A Case Study Using Machine Learning