Artículo: AMZ-B09C38RBQT

Deep Learning in Computational Mechanics: An Introductory Course (Studies in Computational Intelligence Book 977)

Format:

Kindle

Hardcover

Kindle

Paperback

Detalles del producto
Disponibilidad
Sin stock
Peso con empaque
0.20 kg
Devolución
No
Condición
Nuevo
Producto de
Amazon
Viaja desde
USA

Sobre este producto
  • 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. 

Producto prohibido

Este producto no está disponible

Este producto viaja de USA a tus manos en

Conoce más detalles

Highlight, take notes, and search in the book