Deep Learning and Scientific Computing with R torch by Sigrid Keydana (The R Series)
Requirements: .PDF reader, 10 mb
Overview: 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.
Genre: Non-Fiction > Tech & Devices
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.
Download Instructions:
Deep_Learning_and_Scientific_Computing_with_R_torch.pdf
Deep Learning and Scientific Computing with R torch.pdf
