Famous Deep Learning Papers(including Artistic style) in a pseudocode format

I found this GitHub repo that helped me understand artistic style a bit more. There are other papers explained in a pseudo-code format.
I think it will be helpful for people with non math backgrounds.

Delete if already posted


Thanks! This has been super useful in understanding papers. It certainly helps in breaking down the math and the implementation steps.

Thank You @harveyslash . This is very helpful.

I also forked that github and converted all the markdown to ipython notebooks so that it can be easily viewed.
I thought its more convenient this way for the purpose.

If interested you can clone below git


or do it manually using just 2 lines of code:

cd to the original git repo
for i in find . -name "*.md"; do notedown $i > ${i}.ipynb ; done

cd to the readme.md directory
sed -i ā€˜s/.md/.md.ipynb/gā€™ *.ipynb # this is to convert the links from readme so that its easy to navigate