During this comprehensive one-day course, Hugo Schnack, assistant professor Language acquisition, processing and disorders, will introduce the principles of machine learning and explore their relevance for research in the humanities. The day is divided into two parts: an introductory morning session and an optional, more in-depth afternoon session.

Machine learning is a powerful method to discover (complex) patterns in data. It is widely used in fields such as physics, biology, and medicine – and increasingly in the 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 academic research.

Why learn about machine learning?

Machine learning is increasingly used in the humanities for tasks such as:

• Analysing large collections of literary texts or social media data
• Detecting patterns in historical archives
• Studying language change over time
• Recognising objects, handwriting, or artworks in images

What you will learn

Participants will learn how to train, test, and interpret machine learning models using real datasets. You may be surprised to discover how machine learning has already influenced your work, perhaps without your realising it.

While machine learning can offer valuable insights, it should be used with care – like any statistical method. 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.

Programme

This course consists of two sessions, which may be attended separately or together:

• Morning session: Principles
  A general overview of machine learning, its basic principles and a hands-on practical (in R).

• Afternoon session: Practices
  A deeper dive into more advanced topics, and offers more advanced hands-on practicals.

Note that while the morning session is at an introductory level, the afternoon session requires a basic acquaintance with the subject matter. If you are a newcomer to machine learning, the afternoon workshop will be challenging if you have not followed the morning workshop.

Lunch

Lunch is only provided for participants attending both morning and afternoon sessions. Lunch will be served at Espressobar Lodewijk. Dietary preferences can be indicated in the registration form. Coffee and tea will be available throughout the day in the workspace.

Preparation

Please bring your own laptop.

For whom?

Due to our funding, priority is given to UU Humanities scholars and students; a number of seats, however, is reserved for participants from other UU faculties on a first-come, first-serve basis.

If all places are filled, you may email cdh@uu.nl to be placed on the waiting list. Should a place become available, you will be notified.

Registration

To sign up, please complete the registration form below. Register early to secure your place, as spots are allocated on a first-come, first-served basis.

Admission is free, but in providing these workshops, costs are incurred: registration therefore implies a commitment to attend. If you need to cancel, please email to cdh@uu.nl so your spot can be offered to another participant. Thank you for your cooperation.