Description: Natural Language Processing (NLP) is rapidly developing field, with recent advances of deep neural networks that revolutionize many NLP applications. Introduction to wide range of NLP tasks, algorithms for effectively solving these problems (including most recent advances of deep learning models), and methods for evaluating their performance. Focus on statistical and neural-network learning algorithms that train on (annotated) text corpora to automatically acquire knowledge needed to perform task. Lectures discuss general issues and present abstract algorithms. Assignments touch both theoretical foundations of linguistic phenomena and implementation of algorithms. Implemented versions of some algorithms will be provided to give a feel for how systems discussed in class really work, and allow for extensions and experimentation as part of projects.

Units: 4.0