Corona Virus Outbreak Prediction Using Machine Learning

ABSTRACT

Predicting the coronavirus is divided into several parts in this research report, including a state-by-state analysis [2], that includes active, total, cured, and death cases, as well as a daily increase in cases that includes India confirmed, death, and recovered cases. This also includes a thread of new coronavirus cases and forecasts how an outbreak will play out in the next days. This model is implemented using Anaconda navigator and Kaggle, an open-source platform. We utilize Kaggle to forecast time series data in order to predict the virus outbreak. Anaconda Navigator is a free online cloud that gives us with a Jupyter notebook environment that is suited for machine learning ideas. Support Machine learning concepts such as Vector Machine, Regression, and Data Visualization are applied to improve the outcomes of the research. This model includes all available data on the virus's transmission, including total, new, and active cases, as well as forecasting future outbreaks and a weekly epidemic research. © 2022 IEEE.