Articles liés à Deep Learning and Scientific Computing with R torch

Deep Learning and Scientific Computing with R torch - Couverture rigide

Livre 72 sur 73: Chapman & Hall/CRC The R

Keydana, Sigrid

 
9781032231389: Deep Learning and Scientific Computing with R torch
Couverture rigide
ISBN 10 : 1032231386 ISBN 13 : 9781032231389
Editeur : Chapman and Hall/CRC, 2023

Synopsis

torch is an R port of PyTorch, one of the two most-employed deep learning frameworks in industry and research. It is also an excellent tool to use in scientific computations. It is written entirely in R and C/C++.

Though still "young" as a project, R torch already has a vibrant community of users and developers. Experience shows that torch users come from a broad range of different backgrounds. This book aims to be useful to (almost) everyone. Globally speaking, its purposes are threefold:

  • Provide a thorough introduction to torch basics – both by carefully explaining underlying concepts and ideas, and showing enough examples for the reader to become "fluent" in torch
  • Again with a focus on conceptual explanation, show how to use torch in deep-learning applications, ranging from image recognition over time series prediction to audio classification
  • Provide a concepts-first, reader-friendly introduction to selected scientific-computation topics (namely, matrix computations, the Discrete Fourier Transform, and wavelets), all accompanied by torch code you can play with.

Deep Learning and Scientific Computing with R torch is written with first-hand technical expertise and in an engaging, fun-to-read way.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

À propos de l'auteur

Sigrid Keydana is an Applied Researcher at Posit (formerly RStudio, PBC). She has a background in the humanities, psychology, and information technology, and is passionate about explaining complex concepts in a concepts-first, comprehensible way.

À propos de la quatrième de couverture

torch is an R port of PyTorch, one of the two most-employed deep learning frameworks in industry and research. It is also an excellent tool to use in scientific computations. It is written entirely in R and C/C++. Though still "young" as a project, R torch already has a vibrant community of users and developers. Experience shows that torch users come from a broad range of different backgrounds. This book aims to be useful to (almost) everyone. Globally speaking, its purposes are threefold: Provide a thorough introduction to torch basics - both by carefully explaining underlying concepts and ideas, and showing enough examples for the reader to become "fluent" in torch Again with a focus on conceptual explanation, show how to use torch in deep-learning applications, ranging from image recognition over time series prediction to audio classification Provide a concepts-first, reader-friendly introduction to selected scientific-computation topics (namely, matrix computations, the Discrete Fourier Transform, and wavelets), all accompanied by torch code you can play with. Deep Learning and Scientific Computing with R torch is written with first-hand technical expertise and in an engaging, fun-to-read way.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
Chapman and Hall/CRC
Date d'édition
2023
Langue
anglais
ISBN 10 
1032231386
ISBN 13 
9781032231389
Reliure
Relié
Nombre de pages
424
Coordonnées du fabricant
non disponible
Personne responsable
gpsr@libri.de
gpsr@libri.de

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