• Mr. Colin Maclas Gonsalves
• Dr. Prashant Nitnaware

Covid 19 being the global pandemic, it has become an absolute necessity to make sure the epidemic is controlled and the state of the world with respect to health, finance and livelihood come to a better position. The motive of this research aims to contribute towards achieving this state. Every Local Body/Municipality, of a country, needs to be well equipped with the best technology available. Machine learning will play an important role to help Local Body/Municipality predict the trend of Covid19 cases based on the figures collected in their area. This tool will help the Local Body prepare for medical facilities, Administrative decisions and Citizen lifestyle. Making use of five ML algorithms, namely, Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM), FB Prophet, Linear Regression (with FB Prophet) and Random Forest (with FB Prophet). Visualizing the trend on graph, testing the prediction against actual, ruling out the better suited algorithm and using the best of five to predict the coming days. The country's count is derived from the sum of municipal and state statistics. These figures are displayed in front of the entire country to help people comprehend the current situation. There are several web portals that give data visualisation to show the current trend. Some of these sites, such as amso, make predictions based on the information they have. The example of a prediction site is shown above. The municipality-level forecast computation is done in reverse chronological sequence.As a result, when the country's production is conducted as "X," the country data is used to compute the same. The percentage rise or reduction is computed, and the results are applied to the data from the municipality. The same is done for the next 15 to 20 days' worth of data, which is then provided for analysis. Though this is a workaround, it has been in use for quite some time. Because the technology isn't available, the local government must rely on such computations. This study estimates the total number of active cases in India over the next 20 days using machine learning. According to the conclusions of this study, the ARIMA and Random Forest models are most suited to this situation. The model's current-state projection will be beneficial in forecasting the future. Overall, this research can help authorities acquire caution, which could help control the COVID-19 outbreak

"Prediction of Covid-19 Cases Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 10, page no.a518-a528, October-2021, Available :http://www.jetir.org/papers/JETIR2110064.pdf

"Prediction of Covid-19 Cases Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 10, page no. ppa518-a528, October-2021, Available at : http://www.jetir.org/papers/JETIR2110064.pdf