The purpose of this course is to provide an introduction to probabilistic modeling, statistical methods, and their use within the field of language technology. We will cover core foundational concepts in probability theory, linear algebra, calculus, and statistics as time permits.  We will discuss the basics of technologies that apply these areas of mathematics to language (usually via machine learning), such as language modeling.  We will also learn practical skills in programming text processing pipelines for applying statistical natural language processing techniques.

The course syllabus in full as adopted by the head of department is available at the following adress:

 http://kursplaner.gu.se/pdf/kurs/en/LT2212

 http://kursplaner.gu.se/pdf/kurs/sv/LT2212

Course Organizer: Asad Sayeed 

email: asad.sayeed@gu.se

Teaching assistant: Axel Almquist (e-post: axel.almquist@gu.se)

Education coordinator: Madelaine Miller (e-post: madelaine.miller@class.gu.se)

Student Office: Iines Turunen (e-post: iines.turunen@gu.se)

Prel. Schedule (to be updated)

Online guides that will be useful during the course

• Python Programming Language
• Scipy/Numpy Quickstart Tutorial
• Scikit Learn: Machine Learning in Python 
• PyTorch documentation
• NLTK documentation

Note: Canvas Student Guide available at the following Link