Deep Learning and Scientific Computing with R torch

<p>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++.</p><p>Though still young as a project R <i>torch</i> already has a vibrant community of users and developers. Experience shows that <i>torch</i> users come from a broad range of different backgrounds. This book aims to be useful to (almost) everyone. Globally speaking its purposes are threefold:</p><ul> <li>Provide a thorough introduction to <i>torch</i> basics – both by carefully explaining underlying concepts and ideas <i>and</i> showing enough examples for the reader to become fluent in <i>torch</i> </li> <li>Again with a focus on conceptual explanation show how to use <i>torch</i> in deep-learning applications ranging from image recognition over time series prediction to audio classification</li> <li>Provide a concepts-first reader-friendly introduction to selected scientific-computation topics (namely matrix computations the Discrete Fourier Transform and wavelets) all accompanied by <i>torch</i> code you can play with.</li> </ul><p>Deep Learning and Scientific Computing with R torch is written with first-hand technical expertise and in an engaging fun-to-read way.</p>