This repository hosts course materials for AS.360.306/606 Computational Intelligence for the Humanities, an introductory machine learning class for humanities students with a working knowledge of Python designed by Craig Messner.
Upon successful completion of this course, learners will:
- Be able to design basic but meaningful and reproducible computational humanities experiments
- Be able to select and apply appropriate machine learning techniques to humanities research problems
- Understand the theory of language modeling and how it interacts with humanities understandings of language
- Become credibly familiar with the theoretical underpinnings of machine learning and understand how to further their study of its fundamentals
- Produce original research that interacts with the discourse of a humanities field
- Improve their understanding of Python and formal build systems
The course is structured as paired Lecture/Discussion and Lab sections. A lecture/discussion section introduces a concept from ML and its application to the humanities. Its paired lab section presents excercises that build practical competence on top of that theoretical understanding.
The history of computational language modeling serves as an overall throughline for the course.
Currently, this repository houses the LaTeX sourcecode for each module's slides, as well as the .cls file that styles them. This is built on a Beamer backbone.