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Deep Learning and Scientific Computing With R Torch

Deep Learning and Scientific Computing With R Torch

Deep Learning and Scientific Computing With R Torch
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Deep Learning and Scientific Computing With R Torch Hardback - 2023

by Keydana, Sigrid

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Chapman & Hall, 2023. Hardcover. New. 424 pages. 9.19x6.13x1.10 inches.
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Details

  • Title Deep Learning and Scientific Computing With R Torch
  • Author Keydana, Sigrid
  • Binding Hardback
  • Condition New
  • Pages 394
  • Volumes 1
  • Language ENG
  • Publisher Chapman & Hall
  • Publication date 2023
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # x-1032231386
  • ISBN 9781032231389 / 1032231386
  • Weight 1.66 lbs (0.75 kg)
  • Dimensions 9.21 x 6.14 x 0.94 in (23.39 x 15.60 x 2.39 cm)
  • Category Business / Economics / Finance
  • Library of Congress subjects Python (Computer program language), R (Computer program language)
  • Library of Congress Catalogue Number 2022049000
  • Dewey Decimal Code 006.31
  • Quantity available 2

About Revaluation Books Devon, United Kingdom

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From the publisher

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.

About the author

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.

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