Sigrid Keydana

Deep Learning and Scientific Computing with R torch (eBook, ePUB)

• Format: ePub

Produktbeschreibung

This book aims to be useful to (almost) everyone. Deep Learning and Scientific Computing with R Torch provides 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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 414
• Erscheinungstermin: 5. April 2023
• Englisch
• ISBN-13: 9781000863017
• Artikelnr.: 67468884

Autorenporträt

Sigrid Keydana is an Applied Researcher at Posit (formerly RStudio, PBC). She has a background in the humanities, psychology, and information technology, and is passionate about explaining complex concepts in a concepts-first, comprehensible way.

Inhaltsangabe

Part 1. Getting familiar with torch 1. Overview 2. On torch, and how to get
it 3. Tensors 4. Autograd 5. Function minimization with autograd 6. A
neural network from scratch 7. Modules 8. Optimizers 9. Loss functions 10.
Function minimization with L-BFGS 11. Modularizing the neural network Part
2. Deep learning with torch 12. Overview 13. Loading data 14. Training with
luz 15. A first go at image classification 16. Making models generalize 17.
Speeding up training 18. Image classification, take two: Improving
performance 19. Image segmentation 20. Tabular data 21. Time series 22.
Audio classification Part 3. Other things to do with torch: Matrices,
Fourier Transform, and Wavelets 23. Overview 24. Matrix computations:
Least-squares problems 25. Matrix computations: Convolution 26. Exploring
the Discrete Fourier Transform (DFT) 27. The Fast Fourier Transform (FFT)
28. Wavelets