Comprehensive course analysis
About the course
This course covers several important machine learning algorithms for natural language processing that produce state-of-the-art results, including decision trees, k-Nearest Neighbors, Naive Bayes, transformation-based learning, Support Vector Machines, Maximum Entropy and Conditional Random Fields. While the course focuses on supervised methods, it also includes a brief introduction to semi-supervised and unsupervised methods. Students will implement many of the algorithms and apply these algorithms to NLP tasks.
Fei Xia is a professor at the Linguistics Department at the University of Washington (UW) and an adjunct faculty at the Department of Biomedical Informatics and Medical Education at the UW Medical School. Her research covers a wide range of NLP tasks including morphological analysis, part-of-spee...
Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
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