A Repository of Notebooks, Revision notes and Presentation tools for the Explainable AI in Biology Conference in October 2024.
This repository is split into three parts.
This contains a series of Jupyter/iPython notebooks for you to run. They contain a series of tasks and challenges to complete during the Workshop session, culminating in writing a full, trainable Feedforward Neural Network.
If you would like to run these notebooks remotely, visit https://githubtocolab.com/wtsi-hpag/xAIWorkshop.
This is a PDF document (and the requisite LaTeX files used to compile it) containing the following:
- A recap and summary of the important mathematics of Machine Learning, including calculus, linear algebra and optimisation theory.
- Some (largely irrelevant) discussions on the deeper meaning and implications of these mathematics; useful if you found something interesting in the first section!
- A series of notes and explanations which cover the underlying theory which will be discussed during the workshop itself.
It is my hope that you will have been given access to the Recap document early (I did send it to the conference people 2 weeks ago!); but if you don't leave the workshop understanding what has happened, this document is a useful tool to review what it was you learned.
This file contains the PDF and LaTeX documents used to compile the presentation which will be given during the workshop. I can't imagine it being any more useful than the notes, and it's mostly here so that I can have everything in one place, but if you want a PDF of the presentation, it's yours.