CS 7650 - Natural Language Processing
Although this is an in-person course, we plan to stream lectures using Zoom. The link is available here.
Schedule
- Jan 9
- Course Introduction
- Eisenstein Chapter 1
- Jan 11
- Machine Learning
- Eisenstein 2.0-2.5, 4.1,4.3-4.5
- Jan 12
- Problem Set 0 due
- Jan 18
- Machine Learning (multi-class)
- Eisenstein 2.0-2.5, 4.1,4.3-4.5
- Jan 25
- Neural Networks in NLP
- Eisenstein 2.6, 3.1-3.3, J+M 7
- Feb 1
- Sequence Models
- Eisenstein 7.0-7.4, J+M Chapter 8
- Feb 2
- Project 1 due
- Feb 6
- Conditional Random Fields
- Eisenstein 7.5, 8.3
- Feb 15
- Word Embeddings
- Eisenstein 3.3.4, 14.5, 14.6, J+M Chapter 6
- Feb 17
- Problem Set 1 Due
- Feb 20
- Recurrent Neural Networks
- J+M 9.2, 9.4, 9.5, 9.6, Eisenstein 7.6
- Feb 27
- Convolutional Neural Networks and Neural CRFs and Course Projects
- Eisenstein 3.4, 7.6
- March 1
- No Class
- Mar 6
- Neural CRFs and Course Projects
- Eisenstein 3.4, 7.6
- Mar 8
- Statistical Machine Translation
- Eisenstein 18.1, 18.2
- Mar 13
- Encoder-Decoder Networks
- Eisenstein 18.3 - 18.5
- Mar 15
- Neural Machine Translation, Transformers
- Eisenstein 18.3 - 18.5, J+M 10.6
- Mar 16
- Project 2 due
- Mar 27
- Pre-training, BERT
- ELMo BERT
- Mar 29
- Pre-training (cont), BART, T5, GPT-3
- BART, T5, GPT-3
- Mar 31
- Problem Set 2 Due
- Apr 5
- Dialogue
- J+M Chapter 24
- April 12
- Virutal Guest lecture by Sebastian Gehrmann (Bloomberg) - 3:30-4:45pm
- BloombergGPT
- Apr 13
- Project 3 due
- Apr 17
- Question Answering
- J+M Chapter 23
- Apr 19
- Wrapup / QA / Ethics
- Apr 28
- Final Project Reports Due (no late days)