This is the course page for the summer semester 2021 edition of the course statistical natural language processing (NLP) at the Department of Linguistics, University of Tübingen.
This course page is currently under construction. You may want to have a look at the the web page of the previous year’s course for more detailed information on the course content (there will be only some minor changes this semsester).
Course description
This course is a practical, broad and fast-paced introduction to Natural Language Processing (NLP). The course covers a variety of machine learning techniques and their applications in NLP and computational linguistics.
This is a 9ECTS course compulsory for the BA studies in the International Studies in Computational Linguistics (ISCL). Master’s students can take the course as a “Hauptseminar” with additional work (a term project/paper). The course is also open to students of other degree programs with appropriate background. Please contact the instructor before signing up if you are unsure whether you meet the requirements or not. Please see the course syllabus for more information.
Reading material
- Daniel Jurafsky and James H. Martin (2009) Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Pearson Prentice Hall, second edition (JM) chapters from 3rd edition draft (JM3)
- Trevor Hastie, Robert Tibshirani, and Jerome Friedman (2009), The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer-Verlag, second edition. (HTF) available online