Here are my jupyter notebooks on deep learning. All of them are written in pytorch and most of them use the fastai library.

• Using the new training API in fastai.
• Building a simple neural net in pytorch.
• Explore the fastai callback system.

• Neural cache pointer introduce by Grave et al.
• Superconvergence on cifar10 using the 1cycle policy introduce by Leslie Smith
• Deep painterly harmonization from this article
• Adam and weight decay for the correction preoposed in this article

The rest is just a bun of random stuff shared with fellow fastai students.