UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 6
June-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2106427


Registration ID:
310936

Page Number

d195-d201

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Title

Covid-19 outbreak prediction using Machine Learning and Deep Learning

Abstract

Coronavirus Disease 19 or COVID-19 is a highly infectious pandemic caused by novel Coronavirus (SARS Cov 2). The peculiar characteristic of the virus to swiftly proliferate into human existence coupled with scanty data and understanding has resulted in unprecedented mortalities across the globe. With millions of infections and thousands of deaths being reported on daily basis, recording, analyzing and making sense of data in real time significantly aids in combating the virus. This study aims to offer an amicable solution to this problem by developing a prediction model to track the infection and mitigate the risk. A comparative study of legacy Machine Learning algorithms is presented, keeping speed and accuracy in focus. Open-source live data on Covid-19 infections is obtained for prediction and results are presented both worldwide and country-wise.

Key Words

COVID-19, Prediction Model, Machine Learning, SVM, PR, Deep Learning, LSTM.

Cite This Article

"Covid-19 outbreak prediction using Machine Learning and Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.d195-d201, June-2021, Available :http://www.jetir.org/papers/JETIR2106427.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Covid-19 outbreak prediction using Machine Learning and Deep Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppd195-d201, June-2021, Available at : http://www.jetir.org/papers/JETIR2106427.pdf

Publication Details

Published Paper ID: JETIR2106427
Registration ID: 310936
Published In: Volume 8 | Issue 6 | Year June-2021
DOI (Digital Object Identifier):
Page No: d195-d201
Country: Bangalore, Karnataka, India .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


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