Deep Learning And Scientific Computing With R Torch (Chapman & Hall/Crc The R Series)

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.

• | Author: Sigrid Keydana
• | Publisher: Chapman And Hall/Crc
• | Publication Date: Apr 05, 2023
• | Number of Pages: 414 pages
• | Language: English
• | Binding: Hardcover
• | ISBN-10: 1032231386
• | ISBN-13: 9781032231389