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pro vyhledávání: '"Alessya Visnjic"'
Autor:
Alexander Lavin, Ciarán M. Gilligan-Lee, Alessya Visnjic, Siddha Ganju, Dava Newman, Sujoy Ganguly, Danny Lange, Atílím Güneş Baydin, Amit Sharma, Adam Gibson, Stephan Zheng, Eric P. Xing, Chris Mattmann, James Parr, Yarin Gal
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-19 (2022)
The development of machine learning systems has to ensure their robustness and reliability. The authors introduce a framework that defines a principled process of machine learning system formation, from research to production, for various domains and
Externí odkaz:
https://doaj.org/article/5d44c96b0792477fb2fa35f35c38a58a
Autor:
Yarin Gal, Chris A. Mattmann, Alexander Lavin, Danny Lange, Siddha Ganju, Ciarán M. Gilligan-Lee, Sujoy Ganguly, Dava J. Newman, Adam Gibson, Alessya Visnjic, James Parr, Amit Sharma, Eric P. Xing, Atılım Güneş Baydin
The development and deployment of machine learning (ML) systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. The lack of diligence can lead to technical debt, scope creep and misaligned objectives
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be9115224d84198d48754bcd1fbbe4c7
https://doi.org/10.21203/rs.3.rs-133138/v1
https://doi.org/10.21203/rs.3.rs-133138/v1