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Class Schedule

*Class schedule is subject to revision throughout the semester.
WDate Topic Reference Assignment
(due next class)
18/27 (T) Intro to CL, setup, string processing
[Lecture1.pdf]
Python 3 Notes Exercise 1: Python refresher quiz
8/29 (Th) Encoding systems, Python structural programming
[Lecture2.pdf, palindrome]
L&C ch.1 Encoding language Exercise 2: Python quiz, Pig Latin
29/3 (T) Encoding systems & Unicode; text processing with NLTK
[Lecture3.pdf]
NLTK ch.1, ch.2, ch.3 Exercise 3: Processing O. Henry
9/5 (Th) Unicode, spell checking fundamentals: edit distance, more NLTK
[Lecture4.pdf]
L&C ch.2 Writers' aids: spell checkers HW 1: Spell checker, text processing
39/10 (T) N-gram context, n-gram frequency, data resources on web, list comprehension
[Lecture5.pdf]
Exercise 4: Austen vs. Enable
9/12 (Th) Conditional probability, n-gram frequency, conditional frequency distribution
[Lecture6.pdf, CFD + ENABLE practice shell txt/PDF]
NLTK ch.2, ch.3 HW 2: Bigram Speak
49/17 (T) N-gram language models, web resources
[Lecture7.pdf, process Norvig's unigram data txt/PDF]
J&M ed.3 ch.3 N-gram language models Exercise 5: Big-data n-gram stats
9/19 (Th) N-gram resources, NLTK's corpus tools, corpus linguistics
[Lecture8.pdf]
HW 3: BU/JA EFL writing (week-long)
59/24 (T) Type, token, TTR; Zipf's law, freq distribution, n-grams
[Lecture9.pdf]
-
9/26 (Th) HW3 review, classifier intro
[Lecture10.pdf]
NLTK ch.6: 6.1.3 Learning to classify text Exercise 6: Building classifiers
610/1 (T) Naive Bayes classifier
[Lecture11.pdf, name classifier, movie review classifier]
L&C ch.5 Text classification HW 4: Who said it? (week-long)
10/3 (Th) Bayes theorem, evaluation metrics
[Lecture12.pdf]
NLTK 6.5 Naive Bayes classifiers, 6.3 Evaluation -
710/8 (T) Homework 4 review
[Lecture13.pdf]
-
10/10 (Th) Midterm exam Extra credit: Regex preview (due 10/17)
810/15 (T) Fall break
10/17 (Th) Regular expressions
[Lecture14.pdf]
J&M ed.3 ch.2 Regular expressions HW 5: Regular expressions vs Steve Jobs
910/22 (T) Regular expressions
[Lecture15.pdf]
NLTK 3.4 Regular expressions Exercise 7: Regex in Python
10/24 (Th) RE wrap, FSA, FST and Foma
[Lecture16.pdf]
L&C p.218 FSA
Hulden (2011) Morphological analysis with FSTs
Exercise 8: Foma
1010/29 (T) FST & computational morphology
[Lecture17.pdf]
J&M ed.2 (older edition!) ch.3 Words and Transducers
Hulden (2011) Morphological analysis with FSTs
HW 6: Morphological analysis with Foma (week-long)
10/31 (Th) FST and Foma
[Lecture18.pdf]
-
1111/5 (T) POS tags
[Lecture19.pdf]
L&C ch.3.4 POS, Tokenization
NLTK ch.5 Categorizing and tagging words
Exercise 9: POS in Brown Corpus
11/7 (Th) POS tagging
[Lecture20.pdf, Brown & Treebank demo]
NLTK ch.5.5 N-Gram Tagging
J&M ed.3 ch.17 POS tagging
HW 7: N-gram tagger
1211/12 (T) N-gram tagger review, HMM tagger, Trees, CFG
[Lecture21.pdf, lecture21.html]
J&M ed.3 ch.18 CFG & Constituency Parsing
NLTK 7.4.2 Trees!
Exercise 10: Trees
11/14 (Th) Parsing, CFG, Treebanks
[lecture22.html]
NLTK ch.8 Analyzing sentence structure HW 8: CFG and parsing
1311/19 (T) Probabilistic CFG, dependency grammar; Computational semantics: WordNet
[lecture23.html, Lecture23.pdf]
J&M ed.3 ch.19 Dependency parsing
J&M ed.3 ch.G Word sense and WordNet
NLTK 2.5 WordNet
Exercise 11: WordNet, lexical resources
11/21 (Th) Computational semantics: formal, semantic roles
[Lecture24.pdf, PropBank demo]
NLTK ch.10 Analyzing the meaning of sentences
J&M ed.3 ch.21 Semantic role labeling
HW 9: PropBank, word vectors (due 12/5 12/8 Sun 11:59pm)
Thanksgiving break (whole week)
1412/3 (T) Vector semantics, word embeddings
[Lecture25.pdf, Word vectors demo]
L&C ch.4.4 Word meanings as vectors
J&M ed.3 ch.6 Vector semantics and embeddings
-
12/5 (Th) Word vectors wrap, formal language theory
[Lecture26.pdf, same demo JNB from 12/3]
Eisenstein (2019) Ch.9 Formal language theory, draft copy Extra credit: Reflections on NLP, AI (due 12/16, 12/18)
1512/10 (T) Formal language theory
[Lecture27.pdf]
Partee et al. (1993) Ch.16
12/12 (Th) 4pm Final exam
*Class schedule is subject to revision throughout the semester.