ECE 692 001 - Special Topics in Natural Language Processing
Natural language processing (NLP) is an essential part of artificial intelligence (AI), modeling how people share and interpret information expressed in natural human languages. NLP applications cover some of the most important societal domains and disciplines including business, commerce, law, communication, medicine, science, education, and many others. In recent years, applications of deep learning in NLP have spurred an unprecedented innovation and the growth of the NLP-backed state-of-the-art systems.
In this class, we will cover foundational topics in NLP, and we will survey and explore the state-of-the-art advances with Deep Learning.
Students will gain a thorough introduction to cutting-edge research in Deep Learning for NLP through lectures, paper review sessions, and work on the projects.
- An Introduction to Natural Language Processing (NLP)
- A Linguistics Primer
- NLP Pipeline
- Classical NLP vs. Deep Learning-based
- Vector-space based techniques - word embeddings
- Recurrent Neural Networks (brief) and Language Models
- Attention-based Transformers
- Natural Language Generation
- Machine Translation and Question Answering
- 4 quizzes - 20% of the grade
- 2-3 projects - 80% of the grade
All the reading materials, assignments and discussions will be hosted on the course Canvas web page.