A software engineering perspective on engineering machine learning systems: State of the art and challenges

G Giray - Journal of Systems and Software, 2021 - Elsevier
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …
被引用次数：141 相关文章
[PDF] researchgate.net

[PDF][PDF] A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and Challenges

G Giray - researchgate.net
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …

A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and Challenges

G Giray - arXiv preprint arXiv:2012.07919, 2020 - arxiv.org
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …

A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and Challenges

G Giray - arXiv e-prints, 2020 - ui.adsabs.harvard.edu
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …

A software engineering perspective on engineering machine learning systems:: State of the art and challenges

G Giray - 2021 - dl.acm.org
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …

A software engineering perspective on engineering machine learning systems: State of the art and challenges

G Giray - Journal of Systems and Software, 2021 - Elsevier
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of
software development, where algorithms are hard-coded by humans, to ML systems …