Deep learning approaches have surpassed many traditional machine learning methods in recent years in a variety of tasks. Besides for computer vision, this is particularly the case for natural language processing (NLP) and text mining. In this module, we give an introduction to basic concepts of deep learning for natural language processing. To this end, we present NLP tasks and deep learning architecutes used to solve these tasks. We have a detailed look at word embeddings and recurrent neural networks, as well as advanced, state-of-the-art transformer models and generative deep learning approaches.
The module comprises lecture and exercise parts to apply and help deepen the understanding of the presented methods. Further, homework assignments containing both theoretical and practical tasks prepare for the exam.
- Teacher: Aftab Anjum