9783030765866 - deep learning in computational mechanics: an introductory course: 977 di kollmannsberger, stefan; d'angella, davide; jokeit, moritz; herrmann, leon (2 risultati)
Lingua: Inglese
Editore: Springer, Berlin, Springer, 2021
Serie: Libro 481 di 538 - Studies in Computational Intelligence
- Rilegato
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 95,26
EUR 61,71 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Buch. Condizione: 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 t…opics 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.
Lingua: Inglese
Editore: Springer International Publishing Aug 2021, 2021
Serie: Libro 481 di 538 - Studies in Computational Intelligence
- Rilegato
- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 90,94
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Buch. Condizione: 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 overv…iew 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.
