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Deep Learning and Scientific Computing with R torch
Deep Learning and Scientific Computing with R torch
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- More about Deep Learning and Scientific Computing with R torch
Torch is an R port of PyTorch, a deep learning framework used in industry and research. It is written entirely in R and C/C++ and has a vibrant community of users and developers. This book aims to provide a thorough introduction to torch basics, show how to use it in deep-learning applications, and provide a concepts-first, reader-friendly introduction to selected scientific-computation topics.
Format: Paperback / softback
Length: 394 pages
Publication date: 05 April 2023
Publisher: Taylor & Francis Ltd
Torch, an R port of PyTorch, is a highly sought-after deep learning framework in both industry and research. It is also an excellent tool for scientific computations due to its versatility and efficiency. Written entirely in R and C/C++, Torch has already garnered a vibrant community of users and developers.
Despite its relative youth, Torch has already demonstrated its usefulness across a wide range of backgrounds. This book aims to be valuable to nearly everyone, with three primary goals:
Provide a comprehensive introduction to Torch basics, covering underlying concepts and ideas with ample examples to ensure fluency.
Emphasize conceptual explanations, with a focus on providing clear insights rather than overwhelming the reader with technical details.
Show how to use Torch in various deep learning applications, ranging from image recognition to time series prediction and audio classification.
In addition to its introductory content, the book also offers a concepts-first, reader-friendly introduction to selected scientific computation topics, such as matrix computations, the Discrete Fourier Transform, and wavelets. Each topic is accompanied by Torch code that readers can experiment with and play with.
Written with first-hand technical expertise and in an engaging, fun-to-read style, Deep Learning and Scientific Computing with R torch is an invaluable resource for anyone interested in leveraging the power of deep learning and scientific computing in R. Whether you are a data scientist, researcher, or simply someone looking to explore the world of advanced computing, this book will provide you with the knowledge and tools you need to succeed.
Weight: 632g
Dimension: 156 x 234 x 24 (mm)
ISBN-13: 9781032231396
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