Schedule
- Aug 21
- Course Introduction
- Eisenstein Chapter 1
- Aug 23
- Machine Learning
- Eisenstein 2.0-2.5, 4.1,4.3-4.5
- Aug 28
- Machine Learning (multi-class)
- Eisenstein 2.0-2.5, 4.1,4.3-4.5
- Sep 6
- Neural Networks in NLP
- Eisenstein 2.6, 3.1-3.3, J+M 7
- Sep 13
- Sequence Models
- Eisenstein 7.0-7.4, J+M Chapter 8
- Sep 18
- Conditional Random Fields
- Eisenstein 7.5, 8.3
- Sep 19
- Problem Set 1 Due
- Sep 25
- Word Embeddings
- Eisenstein 3.3.4, 14.5, 14.6, J+M Chapter 6
- Oct 2
- Recurrent Neural Networks
- J+M 9.2, 9.4, 9.5, 9.6, Eisenstein 7.6
- Oct 18
- Convolutional Neural Networks and Neural CRFs and Course Projects
- Eisenstein 3.4, 7.6
- Oct 23
- Machine Translation, Encoder-Decoder Networks and Attention
- Eisenstein 18.3 - 18.5
- Oct 30
- MT, Transformers
- Eisenstein 18.3 - 18.5, J+M 10.6
- Nov 1
- Pre-training, BERT
- ELMo BERT
- Nov 8
- Pre-training (cont), BART, T5, GPT-3
- BART, T5, GPT-3
- Nov 13
- Dialogue
- J+M Chapter 24
- Nov 20
- Wrapup / QA / Ethics
- Nov 27
- Virutal Guest lecture by Daniel Deutsch (Google Translate)
- Nov 29
- Virutal Guest lecture by Yi Luan (Google AI Language)