Summer School Machine Learning for Digital Scholarly Editions September 21-25, 2026

Machine learning is increasingly shaping research in the Digital Humanities, offering powerful tools for analyzing and enriching textual data. In this summer school, participants will use the Python library BERTopic to explore various steps of topic modeling. Building upon BERTopic’s modular architecture, students will be introduced to essential machine learning techniques, such as embedding, dimensionality reduction, and clustering.