Natural Language Processing

Catalog description

This course gives an overview of modern data-driven techniques for natural language processing. We will discuss all the steps that are required for NLP such as text classification, neural nets for text classification, language modeling, word embedding, sequence labeling, context free grammar, constituency parsing, dependency parsing syntax, computational ethics, information extraction, conversational agents, machine translation and computational social science.