Published Paper Details:

COVID-19 (Coronavirus) has affected the day to day life of everyone. This disease has affected the lives of thousands of people. COVID-19, described as -'CO' for corona, 'VI' for virus, and 'D' for diseases unfortunately, is rapidly increasing which has put the world in a different state. Broadcasting COVID information and analyzing the present data will help in predicting the future conditions as well as bring a control to this disease. Data Analysis plays an important role in analyzing the data. Data analysis can be done using various machine learning models. Machine learning forecasting models like Dynamic linear models, SIR model , LSTM and GRU model , ARIMA, SARIMA, GARCH, TBATS, Prophet, SIS model, etc. In this study, we used the epidemiological LSTM (Long-short-term-memory) model and GRU (Gated Recurrent unit) model for predicting the spread of COVID-19 cases. It is good to mention here that the forecasts done using these models will be as good as data quality which will be available and, hence, the progress and the prediction can also get affected due to the available quality of the data. The objective of this study is to use the LSTM and GRU model to forecast the analysis and the prediction of COVID -19 cases along with comparison of these two models .This website also provides visual information for better understanding of COVID-19 conditions in India.