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Designing Frameworks for Reliability in Deep Learning Systems
Author(s) -
AYSE ARSLAN
Publication year - 2022
Publication title -
engineering and technology journal
Language(s) - English
Resource type - Journals
ISSN - 2456-3358
DOI - 10.47191/etj/v7i10.07
Subject(s) - deep learning , recommender system , computer science , field (mathematics) , reliability (semiconductor) , context (archaeology) , artificial intelligence , set (abstract data type) , training set , data science , work (physics) , machine learning , engineering , geography , mechanical engineering , power (physics) , physics , mathematics , archaeology , quantum mechanics , pure mathematics , programming language

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