Further reading
Take a look at the following resources to learn more about the topics that were covered in this chapter:
- Official PyTorch Tutorials: https://pytorch.org/tutorials/beginner/basics/intro.html
- Essence of linear algebra, by3Blue1Brown: https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab
- Neural Networks – A Linear Algebra Perspective, by Manu Joseph: https://deep-and-shallow.com/2022/01/15/neural-networks-a-linear-algebra-perspective/
- Deep Learning, by Ian Goodfellow, Yoshua Bengio,and Aaron Courville: https://deep-and-shallow.com/2022/01/15/neural-networks-a-linear-algebra-perspective/
- Understanding LSTMs, by Christopher Olah: http://colah.github.io/posts/2015-08-Understanding-LSTMs/
- Intuitive Guide to Convolution: https://betterexplained.com/articles/intuitive-convolution/
- Computing Receptive Fields of Convolutional Neural Networks, by Andre Araujo, Wade Norris, and Jack Sim: https://distill.pub/2019/computing...
