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Deep Learning and Scientific Computing with R torch.
・ISBN 978-1-032-23139-6 paper GB£ 60.99
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| 著者・編者 | Keydana, Sigrid, |
|---|---|
| シリーズ | (Chapman & Hall/CRC The R Series) |
| 出版社 | (Chapman & Hall/CRC, UK) |
| 出版年月 | 2023 |
| ページ数 | 394 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A01-65777＞ |
解説
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.