Open AccessCovid-19 Analysis and Prediction using Data Science and Machine Learning
Author(s) -
Akshata Kulkarni
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.39272
Subject(s) - covid-19 , computer science , machine learning , predictive modelling , outbreak , regression analysis , artificial intelligence , regression , econometrics , data science , statistics , mathematics , medicine , virology , infectious disease (medical specialty) , disease , pathology
Officials around the world are using several COVID-19 outbreak prediction models to make educated decisions and enact necessary control measures. In this study, we developed a Machine Learning model which predicts and forecasts the COVID-19 outbreak in India, with the goal of determining the best regression model for an in-depth examination of the novel coronavirus. Based on data available from January 31 to October 31, 2020, collected from Kaggle, this model predicts the number of confirmed cases in Maharashtra. We're using a Machine Learning model to foresee the future trend of these situations. The project has the potential to demonstrate the importance of information dissemination in improving response time and planning ahead of time to help reduce risk.