Schedule
- Jan 10
- Course Introduction
- Eisenstein Chapter 1
- Jan 12
- Machine Learning
- Eisenstein 2.0-2.5, 4.1,4.3-4.5
- Jan 14
- Problem Set 1 due
- Jan 17
- MLK Holiday
- Jan 24
- Machine Learning (multi-class) (cont)
- Eisenstein 2.0-2.5, 4.1,4.3-4.5
- Jan 26
- Neural Networks in NLP
- Eisenstein 2.6, 3.1-3.3, J+M 7
- Jan 31
- Sequence Models
- Eisenstein 7.0-7.4, J+M Chapter 8
- Feb 1
- Project 1 Due
- Feb 7
- Conditional Random Fields
- Eisenstein 7.5, 8.3
- Feb 14
- Word Embeddings
- Eisenstein 3.3.4, 14.5, 14.6, J+M Chapter 6
- Feb 16
- Recurrent Neural Networks
- J+M 9.2, 9.4, 9.5, 9.6, Eisenstein 7.6
- Feb 17
- Problem Set 2 Due
- Feb 21
- Convolutional Neural Networks and Neural CRFs
- Eisenstein 3.4, 7.6
- Feb 23
- Neural CRFs (cont.) and Course Projects
- Eisenstein 3.4, 7.6
- Feb 28
- Statistical Machine Translation
- Eisenstein 18.1, 18.2
- Mar 2
- Encoder-Decoder Networks
- Eisenstein 18.3 - 18.5
- Mar 8
- No Class
- Mar 11
- Project 2 Due
- Mar 16
- Neural Machine Translation, Transformers
- Eisenstein 18.3 - 18.5, J+M 10.6
- Mar 28
- Pre-training, BERT
- ELMo BERT
- Mar 30
- Pre-training (cont), BART, T5, GPT-3
- BART, T5, GPT-3
- Apr 4
- Dialogue
- J+M Chapter 24
- Apr 6
- Explanation
- Jain and Wallace, Lipton, Rudin, LIME Blog Post
- Apr 8
- Project 3 Due
- April 11
- Question Answering
- J+M Chapter 23
- Apr 13
- Guest Lecture by Luheng He (Google AI Language)
- Ex2, Retrieval and QA-Based slot filling.
- April 18
- Question Answering (Adversarial, Multi-Hop, etc.)
- J+M Chapter 23
- April 19
- Midterm Due
- April 20
- Wrapup / Multilingual / Ethics
- May 4
- Final Project Reports Due