A tentative plan for the schedule (topics, deadlines, etc.) is available here.
Schedule
- Jan 18
- MLK Holiday
- Jan 20
- Course Introduction
- Eisenstein Chapter 1
- Jan 25
- Machine Learning (Problem Set 1 due)
- Eisenstein 2.0-2.5, 4.1,4.3-4.5
- Jan 27
- Machine Learning (cont)
- Eisenstein 2.0-2.5, 4.1,4.3-4.5
- Feb 3
- Neural Networks in NLP
- Eisenstein 2.6, 3.1-3.3, Goldberg 1-4
- Feb 8
- Sequence Models (Project 1 due)
- Eisenstein 7.0-7.4, J+M Chapter 8
- Feb 15
- Conditional Random Fields
- Eisenstein 7.5, 8.3
- Feb 17
- Word Embeddings (Problem Set 2 due)
- Eisenstein 3.3.4, 14.5, 14.6, J+M Chapter 6, Goldberg 5
- Feb 24
- Recurrent Neural Networks
- J+M 9.2, 9.3, Eisenstein 7.6
- Mar 3
- Convolutional Neural Networks and Neural CRFs
- Eisenstein 3.4, 7.6
- Mar 10
- Statistical Machine Translation
- Eisenstein 18.1, 18.2
- Mar 15
- Project 2 Due
- Mar 17
- Encoder-Decoder Networks
- Eisenstein 18.3 - 18.5
- Mar 24
- Mid-Semester Break (no class)
- Mar 29
- Machine Translation Part 2
- Eisenstein 18.3 - 18.5
- April 4
- Pretrained Transformers
- ELMo BERT
- April 12
- Information Extraction and Semantic Role Labeling
- Eisenstein Chapters 13 & 17
- April 19
- Question Answering (Project 3 Due)
- J+M Chapter 23
- April 21
- Dialogue
- J+M Chapter 24
- April 26
- Wrapup / Ethics
- May 5
- Final Project Reports Due (submit on Gradescope)