If you need immediate technical details rather than a full book, you can find a Deep Learning with Torch Cheat Sheet on , which summarizes model training and tensor operations in just a few pages. AI responses may include mistakes. Learn more Deep Learning and Scientific Computing with R torch

: You can read the complete book for free at skeydan.github.io .

According to the Taylor & Francis eBook and Scribd documentation , these resources typically include:

by Sigrid Keydana (2023): This is the most current and prominent textbook on the subject.

: Tensors, modules, and optimization algorithms.

: Practical implementation of neural network layers like CNNs and LSTMs. Quick Reference Materials

: Matrix computations and Fourier transforms.