Natural language processing (NLP) is the study of computational models of human language, with the ultimate goal of enabling machines to understand and use human language. Due to the presumed connection between human intelligence and human language use, NLP is a core field within artificial intelligence (AI) and currently the focus of significant scientific research, technology development and public interest. The advent of deep learning has seen progress in NLP accelerate over the past years, with numerous major scientific breakthroughs.
This class provides an introductory overview of NLP. We will introduce a range of different NLP tasks such as information extraction, document classification, sequence labeling, machine translation and question-answering, and use these tasks to discuss common challenges and solutions in NLP. This will include methods to learn word and sentence representations, as well as neural architectures for NLP. Since deep learning is now crucial to NLP, the course will include an introduction into the deep learning framework PyTorch. Students will put the covered topics into practice in weekly implementation assigments in Python.
IMPORTANT:
- Students must be enrolled in the practical exercise ("Übung") and successfully participate in exercises and the final exam to pass the course.
- Due to corona, the course will take place online with Zoom.
- Kursverantwortliche/r: Alan Akbik