This repository contains the course projects for CS539 (Statistical Natural Language Processing) at the University of Arizona. The projects are mainly written in python by using the spacy library for natural language processing.
See README files in each project folder for more details.
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.
- Instructor: Dr. Peter Jansen
- Instructor Email: pajansen@arizona.edu
Main python library requirements for the projects are as follows:
spacy
numpy
scipy
scikit-learn