{
"item_title" : "Deep Learning and Scientific Computing with R torch",
"item_author" : [" Sigrid Keydana "],
"item_description" : "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.",
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Deep Learning and Scientific Computing with R torch
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Overview
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.
This item is Non-Returnable
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Details
- ISBN-13: 9781032231396
- ISBN-10: 1032231394
- Publisher: CRC Press
- Publish Date: April 2023
- Dimensions: 9.21 x 6.14 x 0.85 inches
- Shipping Weight: 1.27 pounds
- Page Count: 394
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