Published Paper Details:

COVID-19 outbreak affect human lives as a whole and can be a cause of serious Health Problems and death. Artificial intelligence has been proven to be a effective and powerful tool in the fight against COVID-19 pandemic. Machine learning (ML) models are the most remarkable function in disease prediction, such as the Covid-19, in high geared forecasting and used to help decision-makers to understand future spread of COVID-19. The Aim of this paper is to predict the outbreak of COVID-19 using two approaches of Machine Learning viz. Data Visualization and Prediction using Linear Regression and Support Vector Machine. The models are designed to predict Covid-19, depending on the number of confirmed cases, recovered cases and death cases, based on the available datasets. Support Vector Machine (SVM) and Linear Regression (LR) models were used for this study to predict Covid-19 's risk. Predictions would help to get the future count of the COVID-19 cases and thus to establish precautions before the situation goes out of control. All three cases, such as confirmed, recovered and death, models predict deaths over the next 15 days. The experimental result showed that SVM is doing better than LR to predict the Covid-19 pandemic. According to this report, the pandemic has increased by half between the mid of July 2020. Then we will face a number of hospital shortages, and quarantine place.