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Schedule

Aug 22
Course Introduction
Eisenstein Chapter 1
Aug 24
Machine Learning
Eisenstein 2.0-2.5, 4.1,4.3-4.5
Aug 25
Problem Set 0 due
Aug 29
Machine Learning (cont) (cont)
Eisenstein 2.0-2.5, 4.1,4.3-4.5
Aug 31
Machine Learning (multi-class) (cont)
Eisenstein 2.0-2.5, 4.1,4.3-4.5
Sept 6
Project 0 due
Sept 7
Multi-Class ML (cont.) and Neural Networks in NLP
Eisenstein 2.6, 3.1-3.3, J+M 7
Sept 12
Neural Networks in NLP (Cont)
Eisenstein 2.6, 3.1-3.3, J+M 7
Sept 14
Sequence Models
Eisenstein 7.0-7.4, J+M Chapter 8
Sept 15
Problem Set 1 Due
Sept 19
Conditional Random Fields
Eisenstein 7.5, 8.3
Sept 21
Conditional Random Fields (cont)
Eisenstein 7.5, 8.3
Sept 26
Word Embeddings
Eisenstein 3.3.4, 14.5, 14.6, J+M Chapter 6
Sept 27
Project 1 Due
Sept 28
Word Embeddings (cont)
Eisenstein 3.3.4, 14.5, 14.6, J+M Chapter 6
Oct 3
Recurrent Neural Networks
J+M 9.2, 9.4, 9.5, 9.6, Eisenstein 7.6
Oct 5
Convolutional Neural Networks and Neural CRFs
Eisenstein 3.4, 7.6
Oct 10
Neural CRFs (cont.) and Course Projects
Eisenstein 3.4, 7.6
Oct 12
No Class
Oct 19
Statistical Machine Translation
Eisenstein 18.1, 18.2
Oct 24
Encoder-Decoder Networks
Eisenstein 18.3 - 18.5
Oct 28
Project 2 Due
Oct 31
Neural Machine Translation, Transformers
Eisenstein 18.3 - 18.5, J+M 10.6
Nov 2
Pre-training, BERT
ELMo BERT
Nov 7
Pre-training (cont), BART, T5, GPT-3
BART, T5, GPT-3
Nov 16
Dialogue
J+M Chapter 24
Nov 21
Question Answering
J+M Chapter 23
Nov 22
Project 3 Due Note: Colab notebook version updated on October 31
Nov 28
Wrapup / QA / Ethics
Nov 30
Virutal Guest lecture by Jack Hessel (AI2) - 3:30-4:45pm
Dec 9
Final Project Reports Due (no late days)