CS695-002 Natural Language Processing (Special Topics)
Computers process massive amounts of information every day in the form of human language. Although they do not understand it, they can learn how to do things like answer questions about it, or translate it into other languages. Neural networks provide powerful new tools for modeling language, and have been used both to improve the state-of-the-art in a number of tasks and to tackle new problems that were not easy in the past. This class will start with a brief overview of NLP and Neural Networks, then spend the majority of the class demonstrating how to apply neural networks to natural language problems.
Each section will introduce a particular problem or phenomenon in natural language, describe why it is difficult to model, and demonstrate recent models that were designed to tackle this problem. In the process of doing so, the class will cover different techniques that are useful in creating neural network models, including handling variably sized and structured sentences, semi-supervised and unsupervised learning, structured prediction, and multilingual modeling. The class will include assignments culminating in a final project.
Instructor
Antonios Anastasopoulos (antonis [at] gmu [dot] edu)Office Hours: Online, Tuesday 1-2pm, Thursday 2-3pm. Email for additional appointments.