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pro vyhledávání: '"Alexander Campolo"'
Autor:
Alexander Campolo, Katia Schwerzmann
Publikováno v:
Big Data & Society, Vol 10 (2023)
This paper analyzes the effects of a perceived transition from a rule-based computer programming paradigm to an example-based paradigm associated with machine learning. While both paradigms coexist in practice, we critically discuss the distinctive e
Externí odkaz:
https://doaj.org/article/630fc4a737c043479b23278d8e6d1486
Publikováno v:
Big Data & Society, Vol 10 (2023)
Computer science tends to foreclose the reading of its texts by social science and humanities scholars – via code and scale, mathematics, black box opacities, secret or proprietary models. Yet, when computer science papers are read in order to bett
Externí odkaz:
https://doaj.org/article/1c5254b8fb394c50894c0a9d1ed62390
Autor:
Alexander Campolo
Publikováno v:
KNOW: A Journal on the Formation of Knowledge. 5:83-111
During the past half-century, a set of statistical techniques and ideas about inference have experienced a remarkable scientific success. Significance at the 5 percent level has come to mar...
Autor:
Alexander Campolo
Publikováno v:
Grey Room. 78:34-65
Autor:
Alexander Campolo, Kate Crawford
Publikováno v:
Engaging Science, Technology, and Society, Vol 6, Pp 1-19 (2020)
Deep learning techniques are growing in popularity within the field of artificial intelligence (AI). These approaches identify patterns in large scale datasets, and make classifications and predictions, which have been celebrated as more accurate tha
Publikováno v:
Big Data & Society, 2023, Vol.10(1) [Peer Reviewed Journal]
Computer science tends to foreclose the reading of its texts by social science and humanities scholars – via code and scale, mathematics, black box opacities, secret or proprietary models. Yet, when computer science papers are read in order to bett