Machine learning for NLP 3

SL5CE011

In this course we introduce deep learning methods for natural language processing. The notions of lexical embedding, recurrent networks, sequence-to-sequence transduction models and transformers are presented. Finally, the course presents the interface between deep learning and structured learning methods: labeling of sentences into parts of speech and syntactic analysis. We also introduce transfer learning and the training and usage of pre-trained language models in neural NLP models.