9783030765866 - deep learning in computational mechanics: an introductory course: 977 (studies in computational intelligence, 977) de d’angella, davide; jokeit, moritz; kollmannsberger, stefan (5 resultados)
Deep Learning in Computational Mechanics: An Introductory Course (Studies in Computational Intelligence, 977) 1st ed. 2021 Edition
Kollmannsberger, Stefan; D'Angella, Davide; Jokeit, Moritz; Herrmann, Leon
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 481 de 538 - Studies in Computational Intelligence
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 125,44
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Deep Learning in Computational Mechanics: An Introductory Course (Studies in Computational Intelligence, 977) 1st ed. 2021 Edition
Kollmannsberger, Stefan; D'Angella, Davide; Jokeit, Moritz; Herrmann, Leon
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 481 de 538 - Studies in Computational Intelligence
- Tapa dura
Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 127,42
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Condición: New.
Deep Learning in Computational Mechanics: An Introductory Course (Studies in Computational Intelligence, 977) 1st ed. 2021 Edition
Kollmannsberger, Stefan; D'Angella, Davide; Jokeit, Moritz; Herrmann, Leon
Idioma: Inglés
Editorial: Springer, 2021
Serie: Libro 481 de 538 - Studies in Computational Intelligence
- Tapa dura
Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 130,34
Envío por EUR 9,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New.
Idioma: Inglés
Editorial: Springer, Berlin, Springer, 2021
Serie: Libro 481 de 538 - Studies in Computational Intelligence
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 95,26
Envío por EUR 61,71Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a first course on deep learning in computational mechanics. The book starts with a short introduction to machine learning's fundamental concepts before neural networks are explained thoroughly. It then provides an overview of current to…pics in physics and engineering, setting the stage for the book's main topics: physics-informed neural networks and the deep energy method.The idea of the book is to provide the basic concepts in a mathematically sound manner and yet to stay as simple as possible. To achieve this goal, mostly one-dimensional examples are investigated, such as approximating functions by neural networks or the simulation of the temperature's evolution in a one-dimensional bar.Each chapter contains examples and exercises which are either solved analytically or in PyTorch, an open-source machine learning framework for python.
Idioma: Inglés
Editorial: Springer International Publishing Aug 2021, 2021
Serie: Libro 481 de 538 - Studies in Computational Intelligence
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- Impresión bajo demanda
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 90,94
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a first course on deep learning in computational mechanics. The book starts with a short introduction to machine learning's fundamental concepts before neural networks are explained thoroughly. It then provides an overvi…ew of current topics in physics and engineering, setting the stage for the book's main topics: physics-informed neural networks and the deep energy method.The idea of the book is to provide the basic concepts in a mathematically sound manner and yet to stay as simple as possible. To achieve this goal, mostly one-dimensional examples are investigated, such as approximating functions by neural networks or the simulation of the temperature's evolution in a one-dimensional bar.Each chapter contains examples and exercises which are either solved analytically or in PyTorch, an open-source machine learning framework for python. 112 pp. Englisch.
