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Chameleon: A Semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEs

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dc.contributor.authorOtterbach, Johannes
dc.contributor.authorWollmann, Thomas
dc.date.accessioned2021-12-14T10:57:59Z
dc.date.available2021-12-14T10:57:59Z
dc.date.issued2021
dc.description.abstractDeveloping, scaling, and deploying modern Machine Learning solutions remains challenging for small- and middle-sized enterprises (SMEs). This is due to a high entry barrier of building and maintaining a dedicated IT team as well as the difficulties of real-world data (RWD) compared to standard benchmark data. To address this challenge, we discuss the implementation and concepts of Chameleon, a semi-AutoML framework. The goal of Chameleon is fast and scalable development and deployment of production-ready machine learning systems into the workflow of SMEs. We first discuss the RWD challenges faced by SMEs. After, we outline the central part of the framework which is a model and loss-function zoo with RWD-relevant defaults. Subsequently, we present how one can use a templatable framework in order to automate the experiment iteration cycle, as well as close the gap between development and deployment. Finally, we touch on our testing framework component allowing us to investigate common model failure modes and support best practices of model deployment governance.en
dc.identifier.doi10.18420/informatik2021-097
dc.identifier.isbn978-3-88579-708-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37767
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2021
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-314
dc.subjectSemi-AutoML
dc.subjectproduction systems
dc.subjectIT infrastructure
dc.subjectML development and deployment
dc.subjectcomputer vision
dc.titleChameleon: A Semi-AutoML framework targeting quick and scalable development and deployment of production-ready ML systems for SMEsen
gi.citation.endPage1191
gi.citation.startPage1185
gi.conference.date27. September - 1. Oktober 2021
gi.conference.locationBerlin
gi.conference.sessiontitleWorkshop: Künstliche Intelligenz für kleine und mittlere Unternehmen (KI-KMU 2021)

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P314 - INFORMATIK 2021 - Computer Science & Sustainability