Natural Language Processing

Three credits · Undergraduate

This course presents students with methods to automatically analyze text written in a natural language. It explores traditional statistical methods for natural language processing before focusing on more modern techniques such as embedding-based models. This course represents approaches and their applicability across different tasks, such as, sentiment analysis, machine translation, and document classification. Students are expected to code solutions for assignments and a final project. Prerequisite: CSCI 255; 223 recommended. Three credits. Offered in alternate years.