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portada Deep Learning in Computational Mechanics: An Introductory Course
Type
Physical Book
Author
Publisher
Language
English
Pages
104
Format
Paperback
Dimensions
23.4x15.6x0.6 cm
Weight
0.17 kg.
ISBN13
9783030765897
Categories

Deep Learning in Computational Mechanics: An Introductory Course

Stefan Kollmannsberger (Author) · Davide D'Angella (Author) · Moritz Jokeit (Author) · Springer · Paperback

Deep Learning in Computational Mechanics: An Introductory Course - Kollmannsberger, Stefan ; D'Angella, Davide ; Jokeit, Moritz

New Book Imported to Taiwan
Delivery: 29 Sep - 07 Oct Shipping: 5 to 6 business days.
NT$ 2,885
NT$ 2,885

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Synopsis "Deep Learning in Computational Mechanics: An Introductory Course "

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 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.

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