Machine learning for statistical NLP: advanced
About
In this course, students will get hands-on experience in machine learning for language technology applications, including multimodal applications. This course will cover neural networks and related contemporary techniques and concepts. Students will improve their machine learning skills by developing simple NLP applications in widely-used programming frameworks and get practice in making and implementing design choices independently.
Entry requirements
Admission to the course requires a passed result in each of the following courses:
LT2001 Introduction to programming, 7.5 credits
LT2003 Natural language processing, 15 credits
Admission to the course also requires a passed result in any one of the following courses:
LT2202 Statistical methods, 7.5 credits
LT2212 Statistical methods, 7.5 credits
LT2222 Machine learning for statistical NLP: introduction, 7.5 credits
Language technology skills equivalent to the above will also be accepted for admission.
English proficiency
If you have questions about English proficiency requirements, please contact your international coordinator at the University of Gothenburg.
Application
Do you want to apply for exchange studies at the University of Gothenburg?