9783031190766 - mathematical foundations of data science (texts in computer science) de hrycej, tomas; bermeitinger, bernhard; cetto, matthias; handschuh, siegfried (10 resultados)
Mathematical Foundations of Data Science (Texts in Computer Science)
Hrycej, Tomas; Bermeitinger, Bernhard; Cetto, Matthias; Handschuh, Siegfried
Idioma: Inglés
Editorial: Springer, 2024
Serie: Texts in Computer Science, Libro 75 de 83. Libro 75 de 83 - Texts in Computer Science
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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Condición: New. 2023rd edition NO-PA16APR2015-KAP.
Mathematical Foundations of Data Science
Hrycej, Tomas|Bermeitinger, Bernhard|Cetto, Matthias|Handschuh, Siegfried
Idioma: Inglés
Editorial: Springer, Berlin|Springer International Publishing|Springer, 2024
Serie: Texts in Computer Science, Libro 75 de 83. Libro 75 de 83 - Texts in Computer Science
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Librería: moluna, Greven, Alemaniamoluna
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Kartoniert / Broschiert. Condición: New.
Idioma: Inglés
Editorial: Springer International Publishing Mär 2024, 2024
Serie: Texts in Computer Science, Libro 75 de 83. Libro 75 de 83 - Texts in Computer Science
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This textbook aims to point out the most important principles of data analysis from the mathematical point of view. Specifically, it selected these questions for exploring: Which are the principles necessary to understand the implications of an app…lication, and which are necessary to understand the conditions for the success of methods used Theory is presented only to the degree necessary to apply it properly, striving for the balance between excessive complexity and oversimplification. Its primary focus is on principles crucial for application success.Topics and features:Focuses on approaches supported by mathematical arguments, rather than sole computing experiencesInvestigates conditions under which numerical algorithms used in data science operate, and what performance can be expected from themConsiders key data science problems: problem formulation including optimality measure; learning and generalization in relationships to training set size and number of free parameters; and convergence of numerical algorithmsExamines original mathematical disciplines (statistics, numerical mathematics, system theory) as they are specifically relevant to a given problemAddresses the trade-off between model size and volume of data available for its identification and its consequences for model parametrizationInvestigates the mathematical principles involves with natural language processing and computer visionKeeps subject coverage intentionally compact, focusing on key issues of each topic to encourage full comprehension of the entire bookAlthough this core textbook aims directly at students of computer science and/or data science, it will be of real appeal, too, to researchers in the field who want to gain a proper understanding of the mathematical foundations 'beyond' the sole computing experience.
Idioma: Inglés
Editorial: Springer, 2024
Serie: Texts in Computer Science, Libro 75 de 83. Libro 75 de 83 - Texts in Computer Science
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Librería: preigu, Osnabrück, Alemaniapreigu
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Taschenbuch. Condición: Neu. Mathematical Foundations of Data Science | Tomas Hrycej (u. a.) | Taschenbuch | Texts in Computer Science | xiii | Englisch | 2024 | Springer | EAN 9783031190766 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com |…Anbieter: preigu.
Idioma: Inglés
Editorial: Springer, 2024
Serie: Texts in Computer Science, Libro 75 de 83. Libro 75 de 83 - Texts in Computer Science
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condición: new. Questo è un articolo print on demand.
Mathematical Foundations of Data Science
Hrycej, Tomas; Bermeitinger, Bernhard; Cetto, Matthias; Handschuh, Siegfried
Idioma: Inglés
Editorial: Springer, 2024
Serie: Texts in Computer Science, Libro 75 de 83. Libro 75 de 83 - Texts in Computer Science
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Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International
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Condición: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Idioma: Inglés
Editorial: Springer, Berlin, Springer International Publishing, Springer, 2024
Serie: Texts in Computer Science, Libro 75 de 83. Libro 75 de 83 - Texts in Computer Science
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This textbook aims to point out the most important principles of data analysis from the mathematical point of view. Specifically, it selected these questions for exploring: Which are the principles necessary to understand the implic…ations of an application, and which are necessary to understand the conditions for the success of methods used Theory is presented only to the degree necessary to apply it properly, striving for the balance between excessive complexity and oversimplification. Its primary focus is on principles crucial for application success.Topics and features:Focuses on approaches supported by mathematical arguments, rather than sole computing experiencesInvestigates conditions under which numerical algorithms used in data science operate, and what performance can be expected from themConsiders key data science problems: problem formulation including optimality measure; learning and generalization in relationships to training set size and number of free parameters; and convergence of numerical algorithmsExamines original mathematical disciplines (statistics, numerical mathematics, system theory) as they are specifically relevant to a given problemAddresses the trade-off between model size and volume of data available for its identification and its consequences for model parametrizationInvestigates the mathematical principles involves with natural language processing and computer visionKeeps subject coverage intentionally compact, focusing on key issues of each topic to encourage full comprehension of the entire bookAlthough this core textbook aims directly at students of computer science and/or data science, it will be of real appeal, too, to researchers in the field who want to gain a proper understanding of the mathematical foundations 'beyond' the sole computing experience. 213 pp. Englisch.
Mathematical Foundations of Data Science (Texts in Computer Science)
Hrycej, Tomas; Bermeitinger, Bernhard; Cetto, Matthias; Handschuh, Siegfried
Idioma: Inglés
Editorial: Springer, 2024
Serie: Texts in Computer Science, Libro 75 de 83. Libro 75 de 83 - Texts in Computer Science
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- Impresión bajo demanda
Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 89,31
Envío por EUR 7,65Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. Print on Demand.
Mathematical Foundations of Data Science (Texts in Computer Science)
Hrycej, Tomas; Bermeitinger, Bernhard; Cetto, Matthias; Handschuh, Siegfried
Idioma: Inglés
Editorial: Springer, 2024
Serie: Texts in Computer Science, Libro 75 de 83. Libro 75 de 83 - Texts in Computer Science
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- Impresión bajo demanda
Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 89,61
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Condición: New. PRINT ON DEMAND.
Idioma: Inglés
Editorial: Springer, Springer Mär 2024, 2024
Serie: Texts in Computer Science, Libro 75 de 83. Libro 75 de 83 - Texts in Computer Science
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This textbook aims to point out the most important principles of data analysis from the mathematical point of view. Specifically, it selected these questions for exploring: Which are the principles necessary to understand the implicatio…ns of an application, and which are necessary to understand the conditions for the success of methods used Theory is presented only to the degree necessary to apply it properly, striving for the balance between excessive complexity and oversimplification. Its primary focus is on principles crucial for application success.Topics and features:Focuses on approaches supported by mathematical arguments, rather than sole computing experiencesInvestigates conditions under which numerical algorithms used in data science operate, and what performance can be expected from themConsiders key data science problems: problem formulation including optimality measure; learning and generalization in relationships to training set size and number of free parameters; and convergence of numerical algorithmsExamines original mathematical disciplines (statistics, numerical mathematics, system theory) as they are specifically relevant to a given problemAddresses the trade-off between model size and volume of data available for its identification and its consequences for model parametrizationInvestigates the mathematical principles involves with natural language processing and computer visionKeeps subject coverage intentionally compact, focusing on key issues of each topic to encourage full comprehension of the entire bookAlthough this core textbook aims directly at students of computer science and/or data science, it will be of real appeal, too, to researchers in the field who want to gain a proper understanding of the mathematical foundations 'beyond' the sole computing experience.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 228 pp. Englisch.
