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Deep Learning and Scientific Computing with R torch
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(Buch) |
Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!
Lieferstatus: |
Auf Bestellung (Lieferzeit unbekannt) |
Veröffentlichung: |
April 2023
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Genre: |
Wirtschaft / Recht |
ISBN: |
9781032231396 |
EAN-Code:
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9781032231396 |
Verlag: |
Taylor and Francis |
Einband: |
Kartoniert |
Sprache: |
English
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Dimensionen: |
H 234 mm / B 156 mm / D |
Gewicht: |
580 gr |
Seiten: |
394 |
Illustration: |
Farb., s/w. Abb. |
Bewertung: |
Titel bewerten / Meinung schreiben
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Inhalt: |
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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