Deep Learning and Scientific Computing with R torch: Sigrid Keydana, Boca Raton, FL: Chapman & Hall/CRC Press, 2023, xix + 393 pp., $180.00(H), ISBN: 978-1-032-23138-9.
"Deep Learning and Scientific Computing with R torch" by Sigrid Keydana is a book that introduces an R interface for PyTorch, a popular deep learning framework. The book is well-written and easy to follow, with plenty of illustrations and examples. It is divided into three parts: the basics of torch...
| Publicado en: | American Statistician Vol. 78; no. 2; pp. 264 - 265 |
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| Formato: | Artículo |
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Taylor & Francis Ltd
May2024
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=176695311&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 176695311 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00031305 STT jtl: American Statistician issn: 00031305 maglogo: Y pubinfo: dt: May2024 vid: 78 iid: 2 pid: 377 pub: Taylor & Francis Ltd artinfo: ui: 176695311 10.1080/00031305.2024.2320219 ppf: 264 ppct: 1 formats: tig: atl: Deep Learning and Scientific Computing with R torch: Sigrid Keydana, Boca Raton, FL: Chapman & Hall/CRC Press, 2023, xix + 393 pp., $180.00(H), ISBN: 978-1-032-23138-9. aug: au: Ni, Yang affil: Department of Statistics, Texas A&M University, College Station, TX su: Boca Raton (Fla.) Science education Deep learning Scientific computing Artificial neural networks Convolutional neural networks Torches sug: subj: Boca Raton (Fla.) Science education Deep learning Scientific computing Artificial neural networks Convolutional neural networks Torches ab: "Deep Learning and Scientific Computing with R torch" by Sigrid Keydana is a book that introduces an R interface for PyTorch, a popular deep learning framework. The book is well-written and easy to follow, with plenty of illustrations and examples. It is divided into three parts: the basics of torch, the implementation of deep neural networks, and the utility of torch beyond deep learning. The book covers topics such as tensors, automatic differentiation, neural network architecture, optimization algorithms, and various applications of torch. Overall, it is a valuable resource for R users interested in deep learning and scientific computing. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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