MTH 9796
Statistical Natural Language P · 1.5 credits · Spring 2027
Requirements
Prerequisite: MTH 9893 or equivalent
About this course
This course provides a survey of the challenges, concepts and methodologies employed in Natural Language Processing (NLP). The subject brings together the modeling of the underlying structure of human language with the flexibility and power of neural networks and other algorithmic approaches. The course covers modeling the parts of speech, disambiguation, text similarity, maximum entropy methods, neural networks, and computational semantics.
Seat status as of Oct 2, 10:36 AM ET. Seats can change between refreshes.
2UMA-LEC Seven Wk 2
Mon · 6:05 PM - 9:05 PM
A - 17 Lex 1109
Instructor not announced yetIn PersonOpen