Deep learning and scientific computing with R torch

著者

• Keydana, Sigrid

書誌事項

Deep learning and scientific computing with R torch

Sigrid Keydana

（The R series）

CRC Press, 2023

注記

Includes bibliographical references and index.

収録内容

• Overview
• On torch, and how to get it
• Tensors
• Autograd
• Function minimization with autograd
• A neural network from scratch
• Modules
• Optimizers
• Loss functions
• Function minimization with L-BFGS
• Modularizing the neural network
• Loading data
• Training with luz
• A first go at image classification
• Making models generalize
• Speeding up training
• Image classification, take two: Improving performance
• Image segmentation
• Tabular data
• Time series
• Audio classification
• Matrix computations : Least-squares problems
• Matrix computations : convolution
• Exploring the discrete fourier transform (DFT)
• The fast fourier transform (FFT)
• Wavelets.

• NII書誌ID(NCID): BD06554248
• ISBN:
  • 9781032231396
• LCCN: 2022049000
• 出版国コード: us
• タイトル言語コード: eng
• 本文言語コード: eng
• 出版地: Boca Raton
• ページ数/冊数: xix, 393 pages
• 大きさ: 24 cm
• 分類:
  • LCC : Q325.73
  • DC23 : 006.3/1
• 件名:
  • LCSH : Deep learning (Machine learning)
  • LCSH : Science -- Mathematics -- Data processing
  • LCSH : Python (Computer program language)
  • LCSH : R (Computer program language)
• 親書誌ID:
  • BB06063161