Deep learning and scientific computing with R torch / Sigrid Keydana.
Material type: TextSeries: Chapman & Hall/CRC the R seriesPublisher: Boca Raton : CRC Press, Taylor & Francis Group, 2023Description: 1 online resource : illustrationsContent type:- text
- computer
- online resource
- 9781003275923
- 1003275923
- 9781000862935
- 1000862933
- 9781000863017
- 1000863018
- 006.31 23/eng/20230316
- Q325.73
Item type | Current library | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|
Ebooks | IIM Kashipur | 006.31 (Browse shelf(Opens below)) | Available | E4670 |
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R 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.
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