Deep learning and scientific computing with R torch
著者
書誌事項
Deep learning and scientific computing with R torch
（The R series）
CRC Press, 2023
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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.
