 |
CS
224N -- Ling 237: Natural Language Processing
Spring 2002 Course Materials |
| Handouts |
Some handouts are not available online.
Hard copies of handouts can be found at the Handout Hangout on the first floor of Gates, next
to Gates 182.
- Handout #1: Course Information (HTML)
- Handout #2: Course Syllabus (HTML)
- Lecture notes #1 (Introduction) ps
- Lecture notes #2 (Corpora) ps
- Lecture notes #3 (Text Categorization/Classification) ps
- Lecture notes #3 continued (Naive Bayes example) ps
- Lecture notes #4 (Word sense disambiguation) ps
- Lecture notes #5 (n-gram models and statistical estimation) ps
- Lecture notes #6 (Entropy) ps
- Lecture notes #6 continued (Memory-based learning) ps
- Lecture notes #7 (Tagging and HMMs) ps
- Lecture notes #8 (More on tagging and HMMs) ps
- Lecture notes #9 (Information extraction) ps
- Lecture notes #10 (More on information extraction) ps
- Lecture notes #11 (Basic parsing) ps
- Lecture notes #12 (Chart parsing)
(notes not available online) - Lecture notes #13 (PCFGs) ps
- Lecture notes #14 (Probabilistic parsing) ps
- Lecture notes #15 (Semantics) ps
- Lecture notes #16 (More on semantics) ps
- Lecture notes #17 (Machine translation) ps
- Homework #1: Word
- Word Sense Disambiguation Project: Word or ps
- Solutions to Homework #1: Word or ps
- Homework #2: ps
- Final project: ps
- Homework #3: ps
- Solutions to Homework #2: ps
- Homework #4: ps
- Solutions to Homework #3: ps
- Solutions to Homework #4: ps
- Ken Church tutorial: Unix for poets (pdf or ps)
- What can you do with corpora using just standard Unix command line tools? Word or ps
- Extract of Tom Mitchell's Machine Learning (not available online)
- Tutorial handout: Corpora at Stanford Word or ps
- Example of the EM algorithm for determining lambda weights in a language model (spreadsheet): ComesAcrossLambdaEM.xls
- Textbook website, including in particular, the errata page
- Resources for statistical NLP
- Information Extraction links
- Machine Translation links