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...
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| Veröffentlicht in: | Frontiers in artificial intelligence Jg. 4; S. 667963 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
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Frontiers Media S.A
29.09.2021
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| Schriftenreihe: | Front. Artif. Intell |
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| ISSN: | 2624-8212, 2624-8212 |
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| Abstract | 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. |
|---|---|
| AbstractList | 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.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. 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. 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. This paper is a brief introduction, through a few selected topics, to basic fundamental and practical aspects of TDA for non experts. 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. |
| Author | Chazal, Frédéric Michel, Bertrand |
| AuthorAffiliation | 1 Inria Saclay - Île-de-France Research Centre, Palaiseau , France 2 Ecole Centrale de Nantes, Nantes , France |
| AuthorAffiliation_xml | – name: 1 Inria Saclay - Île-de-France Research Centre, Palaiseau , France – name: 2 Ecole Centrale de Nantes, Nantes , France |
| Author_xml | – sequence: 1 givenname: Frédéric surname: Chazal fullname: Chazal, Frédéric – sequence: 2 givenname: Bertrand surname: Michel fullname: Michel, Bertrand |
| BackLink | https://inria.hal.science/hal-01614384$$DView record in HAL |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 Devendra Singh Dhami, Darmstadt University of Technology, Germany Edited by: Sriraam Natarajan, The University of Texas at Dallas, United States Reviewed by: Ajey Kumar, Symbiosis International (Deemed University), India This article was submitted to Machine Learning and Artificial Intelligence, a section of the journal Frontiers in Artificial Intelligence |
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| Snippet | With the recent explosion in the amount, the variety, and the dimensionality of available data, identifying, extracting, and exploiting their underlying... 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... |
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| Title | An Introduction to Topological Data Analysis: Fundamental and Practical Aspects for Data Scientists |
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