Organization
The course will take place in presence.
- Lecture: Tuesday 13:30-15:10, starting April 16.
- Practice class: No practice class in presence. All information about exercises and homework will be distributed in Moodle.
- Exam
- Date/Time: 29.07.2024
- Room: To be determined
- Moodle Course: Link
- The learning material is available from the Moodle eLeaning platform.
- Requirements
- To pass, each student has to take the written exam at the end of the semester.
- There will also be homework assignments in the practice class which will contribute to your overall grade.
Teaching Staff
- Dr. Thomas Arnold
- Dr. Hendrik Schuff
We currently do not have fixed office hours, so please contact us by mail to get an appointment.
Course content
Main topics
- Deep learning foundations (learning from data, learning problem formalization, loss functions, training with backpropagation, evaluation)
- NLP as supervised task learning
- Language representation (word embeddings, multi-lingual embeddings)
- Prominent architectures (convoluational neural networks, recurrent neural networks)
- Contemporary architectures and foundational models (transformers and BERT)
- Applications (text classification, text generation, translation)