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dc.contributor.authorPinsky, Eugeneen_US
dc.date2020-09-06
dc.date.accessioned2021-04-30T17:39:24Z
dc.date.available2021-04-30T17:39:24Z
dc.date.issued2020-09-06
dc.identifier.citationEugene Pinsky. "Teaching Data Science by History: Kepler's Laws of Planetary Motion and Generalized Linear Models." Computer Science and Education Conference (CSECS 2020). 2020-09-05 - 2020-09-06.
dc.identifier.urihttps://hdl.handle.net/2144/42443
dc.description.abstractTeaching data science is challenging: it is a multidisciplinary subject that requires solid mathematical background. There are many models and approaches to consider. It is important, in our view, to present a unified approach to teaching this subject. We believe that one of the most e ective ways to do so is to present historical examples. An interesting historical example that explains Generalized Linear Models in prediction is the quest by the German astronomer, Johann Kepler, at the beginning of the 17-th century to find a unifying law explaining the motion of the planets in our Solar system.en_US
dc.language.isoen_US
dc.subjectGeneralized linear modelsen_US
dc.subjectPredictionen_US
dc.subjectPlanetary motionen_US
dc.titleTeaching data science by history: Kepler's laws of planetary motion and generalized linear modelsen_US
dc.typeConference materialsen_US
dc.description.versionAccepted manuscripten_US
pubs.elements-sourcemanual-entryen_US
pubs.notesEmbargo: No embargoen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Computer Scienceen_US
pubs.organisational-groupBoston University, Metropolitan Collegeen_US
pubs.publication-statusAccepteden_US
dc.identifier.mycv596576


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