Natural Language Processing

Catalog description

This course introduces Natural Language Processing (NLP), covering its history, fundamental tasks, and challenges due to language ambiguity. Students will explore mathematical foundations (probability and information theory), text representation techniques (bag-of-words, TF-IDF, word embeddings), and neural network architectures, including feed-forward networks and the Transformer model with self-attention.