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An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists

With the recent explosion in the amount, the variety, and the dimensionality of available data, identifying, extracting, and exploiting their underlying structure has become a problem of fundamental importance for data analysis and statistical learning. Topological data analysis (tda) is a recent an...

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Detalles Bibliográficos
Autores principales: Chazal, Frédéric, Michel, Bertrand
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8511823/
https://www.ncbi.nlm.nih.gov/pubmed/34661095
http://dx.doi.org/10.3389/frai.2021.667963
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author Chazal, Frédéric
Michel, Bertrand
author_facet Chazal, Frédéric
Michel, Bertrand
author_sort Chazal, Frédéric
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description With the recent explosion in the amount, the variety, and the dimensionality of available data, identifying, extracting, and exploiting their underlying structure has become a problem of fundamental importance for data analysis and statistical learning. Topological data analysis (tda) is a recent and fast-growing field providing a set of new topological and geometric tools to infer relevant features for possibly complex data. It proposes new well-founded mathematical theories and computational tools that can be used independently or in combination with other data analysis and statistical learning techniques. This article is a brief introduction, through a few selected topics, to basic fundamental and practical aspects of tda for nonexperts.
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spelling pubmed-85118232021-10-14 An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists Chazal, Frédéric Michel, Bertrand Front Artif Intell Artificial Intelligence With the recent explosion in the amount, the variety, and the dimensionality of available data, identifying, extracting, and exploiting their underlying structure has become a problem of fundamental importance for data analysis and statistical learning. Topological data analysis (tda) is a recent and fast-growing field providing a set of new topological and geometric tools to infer relevant features for possibly complex data. It proposes new well-founded mathematical theories and computational tools that can be used independently or in combination with other data analysis and statistical learning techniques. This article is a brief introduction, through a few selected topics, to basic fundamental and practical aspects of tda for nonexperts. Frontiers Media S.A. 2021-09-29 /pmc/articles/PMC8511823/ /pubmed/34661095 http://dx.doi.org/10.3389/frai.2021.667963 Text en Copyright © 2021 Chazal and Michel. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Artificial Intelligence
Chazal, Frédéric
Michel, Bertrand
An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists
title An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists
title_full An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists
title_fullStr An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists
title_full_unstemmed An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists
title_short An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists
title_sort introduction to topological data analysis: fundamental and practical aspects for data scientists
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8511823/
https://www.ncbi.nlm.nih.gov/pubmed/34661095
http://dx.doi.org/10.3389/frai.2021.667963
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