CS333: Natural Language Processing
Natural Language Processing (NLP) is the subfield of CS that focuses on language technology. Because language is one of the most complex human abilities, building computational technologies that involve language is both challenging and important. This course introduces NLP methods and applications.
We will cover a range of techniques, including n-gram models, Bayesian classifiers, neural networks, and deep learning. Applications include parsing, sentiment analysis, machine translation, and language generation, as well as information retrieval tasks like summarization, topic modeling, and question-answering.
Learning Goals
+ Understand and implement core NLP algorithms and models.
+ Explore the challenges posed by different aspects of human language.
+ Analyze ethical concerns about language technology.
+ Complete a series of projects to implement and improve NLP models.
Instructor: Carolyn Anderson
Lecture
M Th 9:55-11:10
SCI L043