This Pre-pre-pre-alpha GitHub template repository includes PLANNED Python library, GNNgraph.py with some basic Sphinx docs ... this is mostly about LEARNING and enjoying learning by exploring a graph, which might be like a syllabus, except that it's more convoluted, branching and tangled ... it is about LEARNING in an autodiadactic hands on manner OR doing things the hard way before making them scale OR proceeding from first principles or from scratch OR taking it step-by-step but paying most attention to the assumptions, rather than narrowing the choices down on a multiple choice test.
The GNNgraph project is about learning how to use data APIs and then wrangling data to be able to parse simple json, csv or minimally formatted txt files into a visual, navigable knowledge-graph.
It's all about the connections and the emergent patterns in data.
Obviously, using reStructuredText to parse this documentation is a deliberate choice which is not just about relying upon the very simple, highly stable docutils codebase.
We envision an annotatable, forkable knowledge-graph which would provide digraph visualization of related modeling approach for comparisons and analyis, as well as ready navigation directly to different executable Python snackable tutorials for learning about how different families of neural network model works ... along with an annotated bibliography of related papers with code and data in the area.
This repository itself began its life as a fork the ReadTheDocs Tutorial. The larger process of how Sphinx works and how forkable tutorial templates like this are built to be integrated with various version control system providers is itself very interesting to anyone exploring how knowledge can be version controlled then forked, shared, work with the universe of Git tools and part of social issues-driven discussion or even pair programming on a platform like GitHub or GitLab... and will be historically, long after after this project is operational.