Analysis of Covid-19 in the United States
using Machine Learning


James G. Koomson, Marymount University, USA


The unprecedented outbreak of COVID-19 also known as the coronavirus has caused a pandemic like none ever seen before this century. Its impact has been massive on a global level. The deadly virus has commanded nations around the world to increase their efforts to fight against the spread of the virus after the stress it has put on resources. With the number of new cases increasing day by day around the world, the objective of this paper is to contribute towards the analysis of the virus by leveraging machine learning models to understand its behavior and predict future patterns in the United States (US) based on data obtained from the COVID-19 Tracking Project.


COVID-19, machine learning, deep learning, prediction, pandemic, linear regression, correlation, SARSCOV-2, Coronavirus Outbreak.