Ingredients for Responsible Machine Learning: A commented Review of the Hitchhiker’s Guide to Responsible Machine Learning

Fernando Marmolejo-Ramos*, Raydonal Ospina, Enrique García-Ceja, Juan C Correa

*Autor correspondiente de este trabajo

Producción científicarevisión exhaustiva

Resumen

In The hitchhiker’s guide to responsible machine learning, Biecek, Kozak, and Zawada (here BKZ) provide an illustrated and engaging step-by-step guide on how to perform a machine learning (ML) analysis such that the algorithms, the software, and the entire process is interpretable and transparent for both the data scientist and the end user. This review summarises BKZ’s book and elaborates on three elements key to ML analyses: inductive inference, causality, and interpretability.
Idioma originalEnglish
Páginas (desde-hasta)175-185
Número de páginas11
PublicaciónJournal of Statistical Theory and Applications
Volumen21
N.º4
DOI
EstadoPublished - dic 2022
Publicado de forma externa

Nota bibliográfica

Publisher Copyright:
© 2022, The Author(s).

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