"Deep Learning for Coders" notebooks with annotations.

The Deep Learning for Coders FastAI course (and its accompannying book) is a fantastic (free!) resource for those looking to get a practical primer on deep learning. However, like pretty much any other course, there are aspects which could be improved: from code readability, to explanations of concepts, to visualizations, etc.; hence my humble contribution in this repository.

This repository collects a set of 20 notebooks (one per chapter of the book) where I retyped all of the code from the original notebooks. In these, I added my own annotations (including code refactorings), links and illustrations, wherever I felt that the original material could benefit from such additions or modifications.

I also added at the end of each notebook my answers to all the questions in the corresponding chapter, as well as my findings from the research challenges.

I created these notebooks to improve my own learning, but I'm making them public here in the hopes that it can be useful for future students of this course. Beware that these notebooks are not a substitute of the original ones but rather a complement. I recommend reading the original book (or equivalently taking the course online), and checking these notebooks whenever you've found something confusing in the code or you want to compare your answers to mine.

If you find inaccuracies of any kind (or any other issue with the notebooks), feel free to open an issue and I'll take a look as soon as I can.

If you're taking the course and have found additional resources that helped you understand a concept in the course more easily, feel free to open a PR (or simply an issue) to add links to such resources. I'll be happy to review them and consider them for inclusion.