Covid-19 Data Analysis using Machine Learning

The COVID-19 epidemic began in Wuhan, China and has now expanded to the majority of a world’s nations. The propagation of a pandemic is primarily determined according to each country’s policies and social responsibilities. As per the WHO, the attack rate for 23 June 2020 is estimated to be between 1.4 and 2.5. In comparison to industrialized nations, India’s position is rather manageable. It would be fascinating to learn about the facts and data surrounding corona cases throughout India. On world meters, many forms of data are provided. We aimed to assess similar information for India and created several predictions on the impacted rate, daily new cases, and daily total completed cases, among others. COVID-19 has cruelly stopped everything within civilization. An examination of COVID-19 records to determine which age groups are the most affected by the virus. Various Machine learning is used to develop predictive model. Algorithms as well as their related performance data are calculated and analysed. Regressor Random Forest and Random Forest The classification algorithm beat all other machine learning algorithm. such as Support Vector Machine, KNN+, Neighbourhood Component Analysis, decision tree classification, and Gaussian Classifier naive Bayesian, Multi linear Regression, various Logistic Classifiers based on the regression technique and the Extreme Gradient Boosting algorithm.