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Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/1084
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dc.contributor.authorNirbhay Narang, Mehul Jangir-
dc.date.accessioned2023-09-15T09:23:21Z-
dc.date.available2023-09-15T09:23:21Z-
dc.date.issued2020-
dc.identifier.urihttp://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/1084-
dc.description.abstractThe outbreak of the novel coronavirus COVID-19 had resulted in deaths of over 24,000 people by April 20, 2020. The goal of this paper is to use and apply principles of statistics and machine learning on COVID-19 datasets available online to predict the inflection point of the spread of the virus. The inflection point, for the purpose of this paper, is defined as a point in time in days after the outbreak of the virus at which there is a change in the direction of the rate of spreading of the virus. We are using available libraries to fit the data a logistic function.en_US
dc.language.isoen_USen_US
dc.publisherIndian Journal of Computer Scienceen_US
dc.subjectCoronavirus,en_US
dc.subjectLogistic functionsen_US
dc.subjectCurve-fittingen_US
dc.subjectInflection pointsen_US
dc.subjectInfection predictionen_US
dc.subjectPythonen_US
dc.titleAnalyzing Data on the Spread of COVID-19 using Statistical Tools to Predict the Inflexion Point of the Virus in Italyen_US
dc.typeArticleen_US
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