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dc.contributor.advisorSteffens, Ulrike-
dc.contributor.authorArslan, Yavuz
dc.date.accessioned2020-09-29T14:56:51Z-
dc.date.available2020-09-29T14:56:51Z-
dc.date.created2019
dc.date.issued2019-02-12
dc.identifier.urihttp://hdl.handle.net/20.500.12738/8607-
dc.description.abstractDie Popularität maschinellen Lernens steigt rasant. Immer mehr Unternehmen nutzen dessen Potenzial, um aus Daten wertvolle Vorhersagen zu generieren. Cloudbasierte Dienste bieten dabei die Chance, die Vorteile maschinellen Lernens leicht und schnell in eigene Anwendungen zu integrieren und gleichzeitig die Vorzüge des Cloud Computing zu nutzen. Diese Thesis untersucht die cloudbasierten Machine Learning Services von Amazon, Google, IBM und Microsoft. Für die Dienste der Gesichts- und Sentimentanalyse werden auÿerdem Tests konzipiert, um die Anbieter untereinander zu vergleichen und sie anhand ihrer Qualität zu bewerten.de
dc.description.abstractPopularity in machine learning rises rapidly as more and more companies use its capabilities to generate useful predictions from data. Cloud-based services o er the opportunity to leverage the benefits of machine learning by providing a simple and quick way to integrate them into applications and simultaneously profit by the advantages of cloud computing. This thesis explores the cloud-based machine learning services from Amazon, Google, IBM and Microsoft. Subsequently, the respective face detection and sentiment analysis services are compared against each other to evaluate their qualities.en
dc.language.isodede
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/-
dc.subject.ddc004 Informatik
dc.titleEvaluierung cloudbasierter Machine Learning Servicesde
dc.typeThesis
openaire.rightsinfo:eu-repo/semantics/openAccess
thesis.grantor.departmentDepartment Informatik
thesis.grantor.placeHamburg
thesis.grantor.universityOrInstitutionHochschule für angewandte Wissenschaften Hamburg
tuhh.contributor.refereeSarstedt, Stefan-
tuhh.gvk.ppn1048944859
tuhh.identifier.urnurn:nbn:de:gbv:18302-reposit-86092-
tuhh.note.externpubl-mit-pod
tuhh.note.intern1
tuhh.oai.showtrueen_US
tuhh.opus.id4531
tuhh.publication.instituteDepartment Informatik
tuhh.type.opusBachelor Thesis-
dc.subject.gndMaschinelles Lernen
dc.type.casraiSupervised Student Publication-
dc.type.dinibachelorThesis-
dc.type.driverbachelorThesis-
dc.type.statusinfo:eu-repo/semantics/publishedVersion
dc.type.thesisbachelorThesis
dcterms.DCMITypeText-
tuhh.dnb.statusdomain-
item.languageiso639-1de-
item.fulltextWith Fulltext-
item.creatorGNDArslan, Yavuz-
item.creatorOrcidArslan, Yavuz-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.openairetypeThesis-
item.advisorGNDSteffens, Ulrike-
item.openairecristypehttp://purl.org/coar/resource_type/c_46ec-
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