Machine Learning for the Humanities

Undergraduate / Graduate

Machine learning is an important aspect of artificial intelligence that uses statistical algorithms to detect patterns in digital data and make predictions on the basis of those patterns, improving the predictions iteratively over time. It is the basis of computer vision (image recognition) and machine translation of natural language (both written texts and sound recordings). So-called deep learning using many-layered neural networks is a subset of machine learning and is the basis of generative AI using large language models (e.g., ChatGPT). This course introduces machine learning with a focus on its uses in the study of human languages, culture, and history in the disciplines of the humanities. Prerequisites: DIGS 20001/30001, "Introduction to Computer Programming Using Python" and DIGS 20002/30002, "Introduction to Statistics Using Python," or equivalent courses in computer programming and statistics.