LING 439/539: Statistical Natural Language Processing
From the course catalog:
This course introduces the key concepts underlying statistical natural language processing. Students will learn a variety of techniques for the computational modeling of natural language, including: n-gram models, smoothing, Hidden Markov models, Bayesian Inference, Expectation Maximization, Viterbi, Inside-Outside Algorithm for Probabilistic Context-Free Grammars, and higher-order language models.
The main programming language used in the course will be Python (3.7).
Please see the course syllabus for details.
MW 9:30AM - 10:45AM in Saguaro Hall, Room 202
In light of this change...
- office hours will be held virtually
- course lectures will be prerecorded and delivered asynchronously for the remainder of the Spring 2020 semester
|Office Hours||MW 10:30AM - 11:30AM and by appointment|
|Office Hours||Thurs 2PM - 3PM|