NLP243: Deep Learning for Natural Language Processing

Introduction to machine learning models and algorithms for natural language processing (NLP) including deep learning approaches. Targeted at professional master's degree students, course focuses 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. (Formerly Machine Learning for Natural Language Processing.) Enrollment is restricted to NLP graduate students.

5 credits

Year	Fall	Winter	Spring	Summer
2024-25	Section 50 Amita Misra (amisra2)
2023-24	Section 50 Ian Lane (ialane)
2022-23	Section 50 Amita Misra (amisra2)
2021-22	Section 50 Dilek Hakkani-Tur (dhakkani)

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