Tentative Schedule

Tuesday	Thursday
8/27 Introduction: Why NLP?	8/29 Regular Expressions & Finite-State Automata Read Chap. 2 Quiz 1
9/3 Language Modeling with N-grams Read Chap. 3 Quiz 2	9/5 Naive Bayes Classification and Sentiment Read Chap. 4
9/10 Logistic Regression Read Chap. 5 Quiz 3	9/12 Vector Semantics and Embeddings Read Chap. 6
9/17 Computing with Word Senses: WSD and WordNet Read Chapter 19 (was Appendix C) Quiz 4	8/19 Neural Nets and Neural Language Models Read Chap. 7
9/24 Part-of-Speech Tagging Read Chap. 8	9/26 Hidden Markov Models Read Appendix A Quiz 5
10/1 Sequence Processing with Recurrent Networks Read Chap. 9	10/3 Constituency Grammars Read Chap. 12 (was 11) Quiz 6
10/8 Constituency Parsing Read Chap. 13 (was 12)	10/10 Statistical Constituency Parsing Read Chap. 14 (was 13) Quiz 7
10/15 Dependency Parsing Read Chap. 15 (was 14)	10/17 Review for Midterm
10/22 Midterm Exam	10/24 Logical Representations of Sentence Meaning Read Chap. 16 (was 15) Quiz 8
10/29 Information Extraction Read Chap. 18 (was 17)	10/31 Semantic Role Labeling and Arugment Structure Read Chap. 20 (was 18)
11/5 Lexicons for Sentiment, Affect, and Connotation Read Chap. 21 (was 19)	11/7 Coreference Resolution Read Chap. 22 (was 20)
11/12 Discourse Coherence Read Chap. 23 (was 21) Quiz 9	11/14 Question Answering Read Chap. 25 (was 23)
11/19 Dialog Systems and Chatbots Read Chap. 26 (was 24)	11/21 Phonetics (new) Read Chap. 27
11/26 Google Translate Read Sequence to Sequence Learning with Neural Networks by Suskever, Vinyals and Le, Google Inc. Read Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation by Wu et al., Google Inc. Neural Machine Translation With Attention Mechanism: Step-by-step Guide has a good introduction to attention mechanisms Understanding Encoder-Decoder Squence to Sequence Model by Simeon Kostadinov is a good intro to Seq2Seq Encoder-Decoder models IBM Model 1 and the EM Algorithm by Huda Khayrallah and Philipp Koehn is a good intro to phrasal alignment models for statistical machine translation	11/28 Thanksgiving Holiday
12/3 IBM Watson Read Building Watson: An Overview of the DeepQA Project from AI Magazine	12/5 Review for Final Exam
12/10 Final Project Presentations	12/12 Final Project Presentations
12/17 Comprehensive Final Exam Tuesday 12:00-2:00 pm (see UHM Final Exam Schedule for other final exam times).

David N. Chin / Chin@Hawaii.Edu