Natural Language Understanding (2015/2016)

Course Overview

This course covers advanced methods in natural language understanding. At its core are methods for learning linguistic representations, at all levels of analysis: lexicon, syntax, semantics, and discourse.

The focus of the course will be on deep learning methods for learning linguistic representations, but standard discriminative and unsupervised methods will also be introduced. We will cover word embeddings, feed-forward neural networks, recurrent neural networks, recursive neural networks, and convolutional neural networks. In addition to the relevant architectures and learning algorithms, we will introduce deep learning approaches to a range of natural language understanding tasks, including language modeling, part-of-speech tagging, parsing, question answering, semantic role labeling, semantic composition, sentiment analysis, and discourse coherence.

Mailing List and Discussion Forum

Announcements regarding the course will be posted to the course mailing list. All students taking the course are automatically subscribed to this list. Previous postings can be accessed using the mailing list archive.

The course uses a Piazza discussion forum for questions relating to the course material or the assignments. If you are enrolled in the course, you should have received an invitation to join Piazza. Contact the lecturers if you haven't received one.

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