Deep Learning and Scientific Computing with R torch

di Sigrid Keydana (Autore)

Taylor & Francis Ltd, 2023

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.

• Autore: Sigrid Keydana
• Editore: Taylor & Francis Ltd
• Collana: Chapman & Hall/CRC The R Series
• Anno: 2023
• Rilegatura: Paperback / softback
• Pagine: 394 p.
• Dimensioni: 234 x 156 mm
• Peso: 580 gr.
• EAN: 9781032231396

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