Steam-powered Turing Machine University of Washington Department of Computer Science & Engineering
CSE 447/547 -- Natural Language Processing [Winter 2020]
Lecture: MWF 10:30pm-11:20am in CSE2 G01
Section: [AA] Thu 12:30pm-1:20pm in MOR220
Section: [AB] Thu 1:30pm-2:20pm in ARCG070
Section: [AC] Thu 2:30pm-3:20pm in MEB242
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Teaching Crew

Personnel Contact Office Hours
Instructor: Yejin Choi yejin at cs dot washington dot edu Tue 4:30pm - 5:30pm @ CSE 578 (and by appointment)
TA: Maxwell Forbes mbforbes at cs dot washington dot edu
Tue 2:30pm - 3:30pm @ CSE2 151 (and by appointment)
TA: Saadia Gabriel skgabrie at cs dot washington dot edu
Thu 10:30am - 11:20am @ CSE2 121 (and by appointment)
TA: Peter West pawest at cs dot washington dot edu
Wed 3:30pm - 4:20pm @ CSE2 153 (and by appointment)
TA: Dianqi Li dianqili at uw dot edu
Tue 10:30 - 11:20am @ CSE2 153 (and by appointment)
TA: Jeff Da jzda at cs dot washington dot edu
Mon 3:30pm - 4:20pm @ CSE2 131 (and by appointment)
TA: Michael Zhang mjqzhang at cs dot washington dot edu
Wed 1:00pm - 2:00pm @ CSE2 121 (and by appointment)

Approximate Schedule

Week Dates Topics & Lecture Slides Notes (Required) Textbook & Recommended Reading
1 Jan 6, 8, 10 I. Introduction [slides]
II. Words: Language Models (LMs) [slides]
LM JM 4.1-4; MS 6
2 Jan 13, 15, 17 II. Words: Unknown Words (Smoothing) [slides]
III. Sequences: Hidden Markov Models (HMMs) [slides]
HMM JM 4.5-7; MS 6; JM 5.1-5.3; 6.1-6.5; MS 9, 10.1-10.3
3Jan 22, 24
(Jan 20: MLK day)
III. Sequences: Hidden Markov Models (HMMs) & EM [slides] Forward-backward, EM JM 6.6-6.8; JM 13-14; MS 11-12
4 Jan 27, 29, 31 *Potential Guest Lecture on Jan 27
IV. Trees: Probabilistic Context Free Grammars (PCFG) [slides]
IV. Trees: PCFG Grammar Refinement [slides]
PCFG, Lexicalized PCFG, Inside-outside
5 Feb 3, 5, 7 IV. Trees: Dependency Grammars [slides]
*Guest Lecture on Feb 7
Edmond-Chu-Liu
6 Feb 10, 12, 14 *Guest Lecture on Feb 10
V. Learning (Feature-Rich Models): Log-Linear Models [slides]
V. Learning (Structural Graphical Models): Conditional Random Fields (CRFs) [slides]
LogLinear MEMMs, CRFs
7 Feb 19, 21
(Feb 17: Presidents Day)
VI. Semantics: From Distributed Semantics to Neural Embeddings [slides]
VII. Deep Learning for NLP
JMv3 Vector Semantics, Dense Vectors JM 19.4; JM 20.7
8 Feb 24, 26, 28 VII. Deep Learning for NLP
9 Mar 2, 4, 6 VII. Deep Learning for NLP
10 Mar 9, 11, 13 VII. Deep Learning for NLP

Textbooks

Assignments, Discussion Board

Available at Canvas

Grading

The grade will consist of homeworks (written & programming) (60%), in-class quizzes (10%), final exam (25%), and course/discussion board participation (5%).

Course Administration and Policies