This intermediate-level course is a continuation of LING 529 and covers a combination of theoretical and applied topics such as (but not limited to) unsupervised learning (clustering), decision trees, and the basics of information retrieval.
Data Types: Numerical, Categorical, Text
Methods: Descriptive statistics, Frequentist inference, Bayesian inference, Machine learning, Data management
Programming Languages: Python, Unix
Course Credits
3