The machine will read and write in our own language, if we can speak its own language. And if we do, it will help us understand our language better, and thus read, understand, and critically assess texts faster, better, and in greater amounts than we could ever do on our own. It will actually be able to do all this for us on its own. That is natural language processing—NLP. And that involves automatically reading countless texts and comparing their most salient features in a matter of seconds. Books, collections, whole libraries, and entire literatures can thus be automatically analyzed and visualized as networks based on these shared or distinctive features. Assembling and exploring those networks is not only incredibly fun, it will also help to better posit the question: what is the most comprehensive meaning of our linguistic textual culture?
Although the course requires a certain amount of coding in Python, no coding skills are assumed.
Number of hours: 18 (1.5 cr.)
Instructor: Chris Tanasescu | Tue – Fri, 09:00 AM – 12:00 PM; Tue – Thu: 02:00 PM – 04:00 PM
Room: MRT 0022 (65 University Private)