Fall 2025 (Sep23-Dec9)
Faculty of Computer Science
Dalhousie University
|
|
[ http://web.cs.dal.ca/~vlado/csci6509/coursecalendar.html ]
Fall 2025 (Sep23-Dec9) Faculty of Computer Science Dalhousie University |
September October November December
Su Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa
1 2 3 4 5 6 1 2 3 4 w2 1 w6 1 2 3 4 5 6 w10
7 8 9 10 11 12 13 5 6 7 8 9 10 11 w3 2 3 4 5 6 7 8 w7 7 8 9 10 11 12 13 w+/ex11-
14 15 16 17 18 19 20 12 13 14 15 16 17 18 w4 9 10 11 12 13 14 15 rw 14 15 16 17 18 19 20 ex
21 22 23 24 25 26 27 w1 19 20 21 22 23 24 25 w5 16 17 18 19 20 21 22 w8 21 22 23 24 25 26 27 ex-21
28 29 30 w2 26 27 28 29 30 31 w6 23 24 25 26 27 28 29 w9 28 29 30 31
30 w10
| # | Date | Title | |
|---|---|---|---|
| Part I: Introduction | |||
| 1 | Tu Sep 23 | Course Introduction
Course introduction: logistics, administrivia, references, evaluation, policies, schedule; Introduction to NLP (reading Ch.1 [JM]): natural language and other languages, NLP applications, NLP as a research area, NLP Research Links and NLP Anthology http://aclweb.org/anthology/. Short history of NLP. NLP methodology overview. Levels of NLP. Files: slides, lecture notes. Reading: [JM] Ch.1 | |
| Part II: Stream-based Text Processing | |||
| 2 | Th Sep 25 | Sources of Complexity in NLP, Course Project, Finite Automata Review (start)
Why is NLP generally hard. Ambiguities at different levels of NLP. About Course Project: topics and teams, deliverables, P0, P1, P, R. Part II: Stream-based Text Processing: Deterministic and Non-deterministic Automata. (Reading: Chapter 2 [JM]) Review of Deterministic Finite Automata (DFA) (start). Files: slides, lecture notes, Syllabus (PDF). | |
| L1 | Mo Sep 29 | Lab 1: FCS Computing Environment, Perl Tutorial 1 Files: lab notes, slides. | |
| Tu Sep 30 | National Day for Truth and Reconciliation, University closed | ||
| 3 | Th Oct 2 | Finite Automata Review Files: slides, lecture notes. | |
| L2 | Mo Oct 6 | Lab 2: Perl Tutorial 2 Files: lab notes, slides. | |
| 4 | Tu Oct 7 | Basic NLP with Perl Files: slides, lecture notes. | |
| 5 | Th Oct 9 | N-grams and Morphology Files: slides, lecture notes. | |
| Fr Oct 10 | P0 Project Topic Proposal due | P0 due | |
| Mo Oct 13 | Thanksgiving Day, University closed | ||
| Part III: Probabilistic and Machine Learning Approach to NLP | |||
| Labs: Python, NLTK, PyTorch | |||
| P0 Topics Discussion; Introduction to Probabilistic Modeling | |||
| Basic Probabilistic Models | |||
| Naive Bayes Model | |||
| N-gram Model | |||
| N-gram Model Smoothing | |||
| POS Tagging and Hidden Markov Model | |||
| Inference with HMMs | |||
| Efficient Inference for Bayesian Networks and HMMs | |||
| Fr Nov 7 | P1 Project Statement due | P1 due | |
| Neural Networks and NLP | |||
| Deep Learning and NLP | |||
| Part IV: Syntactic Processing | |||
| Labs: To Be Decided (possibly Prolog) | |||
| DCG and PCFG | |||
| DCG and PCFG Grammars | |||
| Syntax of Natural Languages; CKY Algorithm | |||
| CKY Algorithm and PCFGs | |||
| Part V: Student Presentations | |||
| Student Presentations | |||
| We Dec 10 | Classes end, Report due | Report due | |
| Final Exam | |||
| ?? Dec ? | Final Exam (TBA)
Final exam, 3 hours; date, time, and location to be announced. Exam period: Dec 11 to Dec 21 (3 hour final exam); Exams schedule URL: http://www.dal.ca/academics/exam_schedule/halifax_campus_exam_schedule.html | F.Exam | |