CSCI1460
Computational Linguistics
Fall 2024
The application of computational methods to problems in natural-language processing. In particular we examine techniques due to recent advances in deep learning: word embeddings, recurrent neural networks (e.g., LSTMs), sequence-to-sequence models, and generative adversarial networks (GANs). Programming projects include sentiment classification, topic modelling and machine translation. Prerequisites are not strictly required, but the course will assume some knowledge of machine learning and deep learning, and will involve programming assignments in Python and PyTorch.
Instructor's Permission Required
Instructor(s): | |
Home Page: | http://cs.brown.edu/courses/csci1460/ |
Meets: | TTh 2:30pm-3:50pm in Smith-Buonanno Hall 106 |
Exam: | No final exam has been scheduled for this course by the department through the registrar's office. Please consult syllabus or contact instructor. If an exam were to have scheduled, it would have been held: |
Max Seats: | 124 Full |
CRN: | 18113 |