Week |
Date |
Topic |
Assignment Out |
Assignment Due |
Lecture Notes |
1 |
08/26 |
Class Outline + Introduction |
Assignment 1 & Final Project Expectation on Team Diversity |
|
Chapter 1 (Jurafsky and Martin) |
1 |
08/28 |
Machine Learning (Binary Classification) |
|
|
classification notes, Eisenstein 2.0-2.6 (Algorithm 5), 4.2-4.4.1, JM 4, JM 5.0-5.5 |
2 |
09/02 |
Machine Learning (Binary/Multiclass Classification) |
|
|
JM 5.6, Eisenstein 4.2, structured SVM secs 1-2 |
2 |
09/04 |
Machine Learning (Multiclass Classification) |
|
|
|
3 |
09/09 |
Sequence Labeling 1: HMMs |
Assignment 2 |
|
Eisenstein 7.0-7.4 (Alg. 11), 8.1, JM 8, Viterbi algorithm lecture note |
3 |
09/11 |
Sequence Labeling 1: HMMs&Sequence Labeling 2: CRFs |
|
Assignment 1 Due |
Sutton CRFs 2.3, 2.6.1, Eisenstein 7.5, 8.3,Wallach CRFs tutorial, Illinois NER |
4 |
09/16 |
Sequence Labeling 2: CRFs |
|
|
Sutton CRFs 2.3, 2.6.1, Eisenstein 7.5, 8.3,Wallach CRFs tutorial, Illinois NER |
4 |
09/18 |
NN1: Feedforward + Word embeddings |
|
|
For Feedforward NNs: Eisenstein 3.0-3.3; Goldberg 1-4, 6; ffnn_example.py; For Word embeddings: Eisenstein 3.3.4, 14.5-14.6, JM 6, Goldberg 5, word2vec, GloVe |
5 |
09/23 |
NN2: RNNs |
|
|
JM 9.1-9.4, Goldberg 10-11 |
5 |
09/25 |
NN4: Language Modeling and Pretraining(Guest Lecture: Xiang Deng) |
|
|
Eisenstein 6, JM 9.2.1, ELMo, BERT, Frozen or fine-tuned |
6 |
09/30 |
Seq2seq 1 + semantic parsing |
Assignment 3 |
|
seq2seq, [Jia and Liang, 2016] |
6 |
10/02 |
Seq2seq 2 (attention) |
|
|
Attention, [Luong Attention], Transformer |
7 |
10/07 |
Syntactics 1: Constituency, PCFGs |
|
Assignment 2 Due |
JM 12.1-12.6, 12.8, JM 14.1-14.4, Eisenstein 10.0-10.5 |
7 |
10/09 |
Syntactics 2: Dependency 1 |
|
|
Eisenstein 11.1-11.2, JM 13.1-13.3, 13.5 |
8 |
10/14 |
Midterm Exam (No Class) |
|
|
Take-home |
8 |
10/16 |
Syntactics 3: Dependency Parsers |
|
|
JM 15.1-15.4 |
9 |
10/21 |
Semantics |
|
Final Project Proposal Due |
|
9 |
10/23 |
Question Answering 1 |
|
|
|
10 |
10/28 |
Question Answering 2 |
|
|
|
10 |
10/30 |
HW and Midterm Discussion and Brief Pytorch Tutorial |
|
|
|
11 |
11/04 |
Dialogue |
|
|
|
11 |
11/06 |
Dialogue & Information Extraction |
|
Assignment 3 Due |
|
12 |
11/11 |
No Class |
|
|
|
12 |
11/13 |
Information Extraction & Pre-trained language models |
|
|
|
13 |
11/18 |
Pre-trained language models & Machine translation |
|
|
|
13 |
11/20 |
Speech recognition |
|
|
|
14 |
11/25 |
Summary + Ethics in NLP |
|
|
|
14 |
11/27 |
No Class |
|
|
|
15 |
12/02 |
Final project presentations |
|
|
|
15 |
12/04 |
Final project presentations |
|
|
|