Please use this identifier to cite or link to this item: https://ir.iimcal.ac.in:8443/jspui/handle/123456789/4874
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dc.contributor.authorPushpam, Parijat
dc.date.accessioned2024-07-11T11:25:56Z
dc.date.available2024-07-11T11:25:56Z
dc.date.issued2023
dc.identifier.urihttps://ir.iimcal.ac.in:8443/jspui/handle/123456789/4874
dc.description.abstractAt the heart of every Machine Learning model lies the fundamental concept of “learning from data.” This singular essence sets Machine Learning apart from conventional programming and ignites our fascination with its potential to revolutionize industries and shape the future. The question is, how do we carry this out? Before answering this question, we should look at a famous scheme or flow of things that are, available in the data science literature everywhere.en_US
dc.language.isoen_USen_US
dc.publisherStudents of PGDBA Post Graduate Diploma in Business Analytics, IIM Calcuttaen_US
dc.relation.ispartofseriesVol.4;
dc.subjectSynthetic dataen_US
dc.subjectAmazon
dc.subjectFraud/Finance
dc.subjectDomain Randomization
dc.subjectBusiness implications
dc.subjectAWS services
dc.subjectGeneral Data Protection Regulation
dc.subjectMachine learning
dc.subjectE-voting
dc.subjectHealthcare data sharing
dc.subjectFinancial transactions
dc.subjectHomomorphic encryption
dc.titleSynthetic Data Generation: robust modelling with limited dataen_US
dc.typeArticleen_US
Appears in Collections:AINA 4.0 - Volume 4 Edition 2022-23

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