Covid 19 Data Analysis in India Using Linear and Polynomial Regression Algorithms
Ekta Rahangdale, Sujata More, Shipali Narnaware, Gayatri Sahu, Sayali Gujar · International Journal for Research in Applied Science and Engineering Technology · 2022
Abstract: In past two years there is a pandemic called covid-19, which has shook the world. The world has suffered a lot and suffering till now by the disastrous effect of corona virus globally. It has affect the world in all parameter i.e. economically, mentally and so on. The world don't when will this pandemic end yet can make forecast by utilizing AI calculations to make moves in the event that this occurs in later days ,how might human and government make counteractions from Covid. This project “Analysis on covid-19 in India using Linear and Polynomial algorithms” analyze the covid-19 datasets from 01-03-2021 to 08-05-2021 for India and also for its top 4 states ,having more number of confirmed cases and predicted the results by using machine learning algorithms (linear regression and polynomial regression with degree of 5).The predicted results will be helpful for government to take actions against this pandemic. Keywords: Data Analysis, Linear Regression, Polynomial Regression, Preprocessing of data, Flask