NLP243: Machine Learning for Natural Language Processing

Introduction to machine learning models and algorithms for Natural Language Processing including deep learning approaches. NLP 243 is a course targeted at Professional MS students, which will focus more on applications and current use of these methods in industry. Topics include an introduction to standard neural network learning methods such as feed-forward neural networks, recurrent neural networks, convolutional neural networks, and encoder-decoder models with applications to natural language processing problems such as utterance classification and sequence tagging. Enrollment is restricted to NLP graduate students.

5 Credits


While the information on this web site is usually the most up to date, in the event of a discrepancy please contact your adviser to confirm which information is correct.