Natural language processing 1000-318bNLP
1. Introduction and Word Vectors
2. Subword Models
3. Linguistic Structure: Dependency Parsing
4. Recurrent Neural Networks and Language Models
5. Machine Translation, Seq2Seq and Attention
6. Attention Mechanism
7. Contextual Representations and Pretraining
8. Dialogue Systems
9. Natural Language Generation
10. Question Answering
11. Multitask Learning
Type of course
Requirements
Course coordinators
Term 2023L: | Term 2024L: |
Learning outcomes
Knowledge: the student
* knows methodologies, topics, techniques and tools in natural language processing [K_W13].
Abilities: the student is able to
* apply in practice techniques of natural language processing [K_U16].
Social competences: the student is ready to
* critically evaluate acquired knowledge and information [K_K01];
* recognize the significance of knowledge in solving cognitive and practical problems and the importance of consulting experts when difficulties arise in finding a self-* devised solution [K_K02];
* think and act in an entrepreneurial way [K_K03].
Assessment criteria
Final grade is based upon the credit programming projects (computer programs) and written as well as oral exam.
Bibliography
Dan Jurafsky and James H. Martin. Speech and Language Processing
Jacob Eisenstein. Natural Language Processing
Yoav Goldberg. A Primer on Neural Network Models for Natural Language Processing
Ian Goodfellow, Yoshua Bengio, and Aaron Courville. Deep Learning
Delip Rao and Brian McMahan. Natural Language Processing with PyTorch
Additional information
Information on level of this course, year of study and semester when the course unit is delivered, types and amount of class hours - can be found in course structure diagrams of apropriate study programmes. This course is related to the following study programmes:
- Bachelor's degree, first cycle programme, Computer Science
- Master's degree, second cycle programme, Computer Science
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: