Deep Learning and Scientific Computing with R torch

By: Sigrid Keydana

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Paperback | 5 April 2023 | Edition Number 1

At a Glance

Paperback
414 Pages

Dimensions(cm)
23.39 x 15.6 x 2.16

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$207.75

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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.

Industry Reviews

"The book is very well written and easy to follow with plenty of illustrations and explanations via examples and codes. I have learned a lot from the book and believe that many R users can greatly benefit from it as well even without an extensive machine learning background."

- Yang Ni, Texa A&M University, U.S.A, The MAerican Statistician, April 2024

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