dc.contributor.author | Muiruri, Dennis | |
dc.contributor.author | Lwakatare, Lucy Ellen | |
dc.contributor.author | Nurminen, Jukka K. | |
dc.contributor.author | Mikkonen, Tommi | |
dc.date.accessioned | 2022-10-21T11:24:11Z | |
dc.date.available | 2022-10-21T11:24:11Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | Muiruri, D., Lwakatare, L. E., Nurminen, J. K., & Mikkonen, T. (2022). Practices and Infrastructures for Machine Learning Systems : An Interview Study in Finnish Organizations. <i>Computer</i>, <i>55</i>(6), 18-29. <a href="https://doi.org/10.1109/mc.2022.3161161" target="_blank">https://doi.org/10.1109/mc.2022.3161161</a> | |
dc.identifier.other | CONVID_146545532 | |
dc.identifier.uri | https://jyx.jyu.fi/handle/123456789/83628 | |
dc.description.abstract | Using interviews, we investigated the practices and toolchains for machine learning (ML)-enabled systems from 16 organizations across various domains in Finland. We observed some well-established artificial intelligence engineering approaches, but practices and tools are still needed for the testing and monitoring of ML-enabled systems. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | |
dc.relation.ispartofseries | Computer | |
dc.rights | CC BY 4.0 | |
dc.subject.other | organizations | |
dc.subject.other | machine learning | |
dc.subject.other | learning systems | |
dc.subject.other | monitoring | |
dc.subject.other | artificial intelligence | |
dc.subject.other | interviews | |
dc.subject.other | software engineering | |
dc.subject.other | business practices | |
dc.subject.other | computational modeling | |
dc.subject.other | data models | |
dc.title | Practices and Infrastructures for Machine Learning Systems : An Interview Study in Finnish Organizations | |
dc.type | article | |
dc.identifier.urn | URN:NBN:fi:jyu-202210214943 | |
dc.contributor.laitos | Informaatioteknologian tiedekunta | fi |
dc.contributor.laitos | Faculty of Information Technology | en |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | |
dc.type.coar | http://purl.org/coar/resource_type/c_2df8fbb1 | |
dc.description.reviewstatus | peerReviewed | |
dc.format.pagerange | 18-29 | |
dc.relation.issn | 0018-9162 | |
dc.relation.numberinseries | 6 | |
dc.relation.volume | 55 | |
dc.type.version | publishedVersion | |
dc.rights.copyright | © Authors, 2022 | |
dc.rights.accesslevel | openAccess | fi |
dc.subject.yso | älytekniikka | |
dc.subject.yso | haastattelututkimus | |
dc.subject.yso | tekoäly | |
dc.subject.yso | monitorointi | |
dc.subject.yso | liiketoimintaprosessit | |
dc.subject.yso | organisaatiot | |
dc.subject.yso | ohjelmistotuotanto | |
dc.subject.yso | koneoppiminen | |
dc.format.content | fulltext | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p27260 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p10632 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p2616 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p3628 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p24272 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p272 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p17097 | |
jyx.subject.uri | http://www.yso.fi/onto/yso/p21846 | |
dc.rights.url | https://creativecommons.org/licenses/by/4.0/ | |
dc.relation.doi | 10.1109/mc.2022.3161161 | |
jyx.fundinginformation | This work was supported in part by local authorities (Business Finland) under grant agreements ITEA-2019-18022-IVVES https://ivves.eu/ ITEA3 program and ITEA-2021-20219-IML4E https://iml4e.org/ of ITEA4 program. | |
dc.type.okm | A1 | |