The COVID-19 pandemic has led to a dramatic loss of human life worldwide and presents an unprecedented challenge to public health, food systems, and therefore the world of labor. India had its first case of Covid 19 on 30th January 2020. Cases of the COVID-19 pandemic are exponentially increasing day by day within the whole world. As of June 2020, India has the 2nd highest number of confirmed cases in the world. It has become important to reduce the number of cases and save as many lives as possible. Therefore, if the number of deaths is predicted early, Millions of lives could be saved. Government can predict the spread of infections, resulting in better planning of resources, better preparedness for response, and improved health care facilities. Machine learning plays a very important role in pandemic situations such as predicting the future death toll, cured cases, and thereby planning further measures based on these predictions. Many models of machine learning have been proposed by various authors in the literature. This motivated us to present a survey of those models and implement them for comparison in this work.