Covid-19 Pandemic Data Analysis and Forecasting using Machine Learning Algorithms

India reported its first case of covid-19 on 30th Jan 2020. Though we did not notice a significant rise in the number of cases in the month of February and like many other countries, this number escalated like anything from March 2020. This research paper will include analysis of covid-19 data initially at a global level and then drilled down to the scenario of India. Data is gathered from multiple data sources from several authentic government websites. The paper will also include analysis of various features like gender, geographical location, age using Python and Data Visualization techniques. Getting insights on Trend pattern and time series analysis will bring more clarity to the current scenario as analysis is totally on real-time data(till 19th June). Finally we will use some machine learning algorithms and perform predictive analytics of the near future scenario. We are using a sigmoid model to give an estimate of the day on which we can expect the number of active cases to reach its peak and also when the curve will start to flatten sigmoid model gives us a count of date which is a unique feature of analysis in this paper. We are also using certain feature engineering techniques to transfer data into logarithmic scale for better comparison removing any data extremities or outliers. Based on the predictions of the short-term interval, our model can be tuned to forecast long time intervals. Needless to mention there are a lot of factors responsible for the cases to come in the upcoming days. It depends on the people of the country and how strictly they obey the rules and restriction imposed by the Government.