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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.
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