This repository includes the jupyter notebooks for the 2021 Workshop "Mathematical and Computational Methods for Complex Social Systems" to be held at the virtual JMM 2021, led by Elizabeth Munch. This introduction is tailored for a network science audience, so the focus is on an relevant tools when given a network input.
The goals of this 1-hour introduction are:
- Give a brief overview of available packages
- Provide pipelines for computing persistent homology for input data such as a discrete metric space and a weighted graph.
- Show some basic ways to interface with machine learning toolkits
As is true in a normal year and worse in a pandemic year, I'm super late writing this talk. So, if you're looking at this before the actual tutorial is running (1:30 EST Tuesday, Jan 5), it's likely not finished. Take everything with a grain of salt!
To run the notebook online, no installs necessary, click here:
Please feel free to get in touch if you have questions, in particular about TDA and applications: muncheli@msu.edu