Stony Brook University, Computer Science
As humans, we seemingly process language quite effortlessly, but getting computers to understand natural language is one of the grand challenges of AI and its pursuit has resulted in methods that largely power some of the key technologies of the modern digital world such as chatbots, web search, translation, and personal assistants (e.g. Siri, Alexa). This course will introduce the algorithms and statistical techniques used for natural language processing, covering syntax (identifying structure), semantics (uncovering meaning), and applications (e.g. sentiment analysis, question answering, and human language analysis). Students will implement the techniques in modern machine learning that power state-of-the-art NLP: maximum entropy learners (logistic regression), transformers, and the attention mechanism and deploy them in modern applications.