During this comprehensive one-day course, Hugo Schnack, assistant professor Language acquisition, processing and disorders, will give an introduction to machine learning and explore its applications and potential within the humanities.

Machine learning is a data analysis technique to discover (complex) patterns within datasets. These techniques have found their application in many (research) areas, ranging from physics, biology, medicine, and, of course, humanities. In this tutorial, Schnack will guide you through some appealing (and appalling!) machine learning examples from literature, examples from his own research, and current use and potential applications in humanities research.

Participants will engage in hands-on activities, learning to train, test, and interpret machine learning models using (real) datasets. Discover how some kind of machine learning has likely already played a role in your work, without you knowing it. While machine learning is a powerful tool to extract useful information from data and obtain valuable insights, it should be used with care – like any statistics. Schnack will try to teach you a critical attitude towards machine learning, discussing common pitfalls and arguing that human intelligence is still necessary to obtain valid and reliable results.

Level

This is a beginners workshop, but a basic understanding of statistics and R is beneficial. Even without this basic knowledge, you are welcome to attend, but then be aware that this workshop will be a bit more challenging.

Target audience

Due to our funding, priority will be given to humanities teachers, researchers, and students for this workshop. If you are affiliated with a different faculty or institution but interested in participating, please register to be placed on a waiting list. Notification of available spaces will be sent two weeks before the workshop.

To secure your spot, we encourage you to register as soon as possible, as registrations will be processed on a first-come, first-served basis. If you find yourself unable to attend, we kindly request that you cancel your registration by sending an email to CDH@uu.nl. This will allow us to offer the spot to another interested participant. Thank you for your cooperation.