Texts in computer science - 9783031190735 - mathematical foundations of data science (texts in computer science) de hrycej, tomas; bermeitinger, bernhard; cetto, matthias; handschuh, siegfried (13 resultados)
Idioma: Inglés
Editorial: Springer, 2023
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Librería: WorldofBooks, Goring-By-Sea, WS, Reino UnidoWorldofBooks
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EUR 50,57
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Paperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Idioma: Inglés
Editorial: Springer, 2023
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Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de AmericaWorld of Books (was SecondSale)
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EUR 80,50
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Condición: Good. Good condition ex-library book with usual library markings and stickers.
Idioma: Inglés
Editorial: Springer International Publishing AG, Cham, 2023
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 80,51
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Hardcover. Condición: new. Hardcover. 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 application, and which are necessary to underst…and 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Editorial: Springer, 2023
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Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International
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EUR 80,52
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Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Idioma: Inglés
Editorial: Springer, 2023
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 79,79
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Condición: New. 1st Edition.
Idioma: Inglés
Editorial: Springer, 2023
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 77,91
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Condición: New.
Idioma: Inglés
Editorial: Springer, 2023
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 79,85
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Condición: New.
Idioma: Inglés
Editorial: Springer, 2023
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 89,86
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Hardcover. Condición: Brand New. 226 pages. 9.25x6.10x0.71 inches. In Stock.
Mathematical Foundations of Data Science
Hrycej, Tomas|Bermeitinger, Bernhard|Cetto, Matthias|Handschuh, Siegfried
Idioma: Inglés
Editorial: Springer, Berlin|Springer International Publishing|Springer, 2022
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Librería: moluna, Greven, Alemaniamoluna
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EUR 77,17
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Gebunden. Condición: New.
Idioma: Inglés
Editorial: Springer International Publishing AG, Cham, 2023
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 99,50
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Hardcover. Condición: new. Hardcover. 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 application, and which are necessary to underst…and 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Idioma: Inglés
Editorial: Springer, 2023
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 98,82
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Buch. 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 applicatio…n, 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 International Publishing Mrz 2023, 2023
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 90,94
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Buch. 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 implications…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. 228 pp. Englisch.
Idioma: Inglés
Editorial: Springer, Springer Mär 2023, 2023
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 90,94
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. 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 implications of a…n 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.
