• Saridi Devendra Kumar
• Prof D Lalitha Bhaskari

Nowadays, there is a very adverse impact on economic, cultural, social and almost all fields in the world because of Covid-19. The Covid-19 term is described as -'CO' for corona, 'VI' for virus, and 'D' for disease. It is an infectious disease caused by severe acute respiratory syndrome which is transmitted through respiratory droplets and contact routes. Since December 2019, corona-virus disease (COVID-19) has out-broke from the country China. The spread of COVID-19 in the whole world has put humanity at risk. The resources of some of the largest economies are stressed out due to the large infectivity and transmissibility of this disease. Due to the growing magnitude of number of cases and its subsequent stress on the administration and health professionals, some prediction methods would be required to predict the number of cases in future. In this paper, we have used data-driven estimation methods like Random Forest- regression, XGBoost, LightGBM and prophet for prediction of the number of COVID-19 cases in India: 15 days ahead and also compares India with the worldwide data and the effect of preventive measures like social isolation and lockdown and the number of tests being conducted on the spread of COVID-19. The prediction of various parameters (total number of cases, number of positive cases etc.) obtained by the proposed method is accurate within a certain range and will be a beneficial tool for administrators and health officials

Covid, CoronaVirus, Random Forest- regression, XGBoost, Prophet, LightGBM, evaluation metrics. Prediction

"Prediction for the spread of COVID-19 in India using Machine Learning Methods", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 10, page no.2873-2880, October-2020, Available :http://www.jetir.org/papers/JETIR2010375.pdf

"Prediction for the spread of COVID-19 in India using Machine Learning Methods", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 10, page no. pp2873-2880, October-2020, Available at : http://www.jetir.org/papers/JETIR2010375.pdf