All the Python packages presented in this blog:

• nnetsauce   Statistical/Machine Learning using Randomized and Quasi-Randomized (neural) networks  |  feedback form
• querier   A query language for Python Data Frames  |  feedback form
• mlsauce   Miscellaneous Statistical/Machine Learning stuff  |  feedback form
• teller   Model-agnostic Statistical/Machine Learning explainability  |  feedback form

Now have a common home for their documentation, available
on Techtonique website (it’s a work in progress).

Figure: New Techtonique Website

For this documentation, I’m using MkDocs in conjunction with
keras-autodoc. With MkDocs,
I found out that you can create a static website rapidly using Markdown. Regarding package technical
documentation in particular, one thing that I find useful and that I’ve been
searching for a while, is the ability for a tool to loop and read Python docstrings: that’s what
keras-autodoc allowed me to do. I’ve heard of a way of doing such a thing for R documentation recently:

So, cross_val and ESGtoolkit, two
R members of Techtonique, are next in line for Techtonique website.
I may also give pkgdown a try, depending on how
I’m able to tweak the styles, and all.