Ingredients for Responsible Machine Learning: A Commented Review of The Hitchhiker’s Guide to Responsible Machine Learning

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 fo...

Descripción completa

Detalles Bibliográficos
Autores principales: Marmolejo-Ramos, Fernando, Ospina, Raydonal, García-Ceja, Enrique, Correa, Juan C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2022
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9483296/
https://www.ncbi.nlm.nih.gov/pubmed/36160758
http://dx.doi.org/10.1007/s44199-022-00048-y
_version_ 1784791641856409600
author Marmolejo-Ramos, Fernando
Ospina, Raydonal
García-Ceja, Enrique
Correa, Juan C.
author_facet Marmolejo-Ramos, Fernando
Ospina, Raydonal
García-Ceja, Enrique
Correa, Juan C.
author_sort Marmolejo-Ramos, Fernando
collection PubMed
description 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.
format Online
Article
Text
id pubmed-9483296
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Springer Netherlands
record_format MEDLINE/PubMed
spelling pubmed-94832962022-09-19 Ingredients for Responsible Machine Learning: A Commented Review of The Hitchhiker’s Guide to Responsible Machine Learning Marmolejo-Ramos, Fernando Ospina, Raydonal García-Ceja, Enrique Correa, Juan C. J Stat Theory Appl Review 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. Springer Netherlands 2022-09-15 2022 /pmc/articles/PMC9483296/ /pubmed/36160758 http://dx.doi.org/10.1007/s44199-022-00048-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Review
Marmolejo-Ramos, Fernando
Ospina, Raydonal
García-Ceja, Enrique
Correa, Juan C.
Ingredients for Responsible Machine Learning: A Commented Review of The Hitchhiker’s Guide to Responsible Machine Learning
title Ingredients for Responsible Machine Learning: A Commented Review of The Hitchhiker’s Guide to Responsible Machine Learning
title_full Ingredients for Responsible Machine Learning: A Commented Review of The Hitchhiker’s Guide to Responsible Machine Learning
title_fullStr Ingredients for Responsible Machine Learning: A Commented Review of The Hitchhiker’s Guide to Responsible Machine Learning
title_full_unstemmed Ingredients for Responsible Machine Learning: A Commented Review of The Hitchhiker’s Guide to Responsible Machine Learning
title_short Ingredients for Responsible Machine Learning: A Commented Review of The Hitchhiker’s Guide to Responsible Machine Learning
title_sort ingredients for responsible machine learning: a commented review of the hitchhiker’s guide to responsible machine learning
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9483296/
https://www.ncbi.nlm.nih.gov/pubmed/36160758
http://dx.doi.org/10.1007/s44199-022-00048-y
work_keys_str_mv AT marmolejoramosfernando ingredientsforresponsiblemachinelearningacommentedreviewofthehitchhikersguidetoresponsiblemachinelearning
AT ospinaraydonal ingredientsforresponsiblemachinelearningacommentedreviewofthehitchhikersguidetoresponsiblemachinelearning
AT garciacejaenrique ingredientsforresponsiblemachinelearningacommentedreviewofthehitchhikersguidetoresponsiblemachinelearning
AT correajuanc ingredientsforresponsiblemachinelearningacommentedreviewofthehitchhikersguidetoresponsiblemachinelearning

Ejemplares similares