Links to the course material will be provided in the schedule below after each class. You may want to have a look at the previous edition of the course for reference.
Reading material
- Daniel Jurafsky and James H. Martin (2009) Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition. Pearson Prentice Hall, second edition (JM) chapters from 3rd edition draft (JM3)
- Trevor Hastie, Robert Tibshirani, and Jerome Friedman (2009), The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer-Verlag, second edition. (HTF) available online
The course schedule
| Week | Monday | Wednesday | Friday |
|---|---|---|---|
| 01 | Apr 16 No class |
Apr 18 Introduction [slides, 8up] |
Apr 20 Python refresher (I) [slides, exercises, sol(raw), sol(view)] |
| 02 | Apr 23 Background: math [slides, 8up] |
Apr 25 Python refresher (II) [slides] |
Apr 27 Background: prob. theory [slides, 8up] |
| 03 | Apr 30 Background: inf. theory [slides, 8up] |
May 02 Exercises |
May 04 ML Intro / regression |
| 04 | May 07 Regression [slides, 8up] Reading: HTF 3.2 & 3.4 |
May 09 Exercises |
May 11 Classification [slides, 8up] Reading: JM 6.6 (JM3 Ch.7), HTF 4.4 |
| 05 | May 14 Classification / ML evaluation |
May 16 A1 discussion, exercises [slides] |
May 18 ML evaluation [slides, 8up] |
| May 21 No class |
May 23 No class |
May 25 No class |
|
| 06 | May 28 Summary [sample questions] |
May 30 Exercises |
Jun 01 Sequence learning [slides, 8up] Reading: JM3 Ch.9, HTF 4.4 |
| 07 | Jun 04 Unsupervised learning [slides, 8up] |
Jun 06 A2 discussion, review questions, exercises [a2, review] |
Jun 08 Neural Networks (1) [slides, 8up] |
| 08 | Jun 11 Neural networks (2) |
Jun 13 Exercises |
Jun 15 Neural Networks (3) |
| 09 | Jun 18 Tokenization/segmentation [slides, 8up] |
Jun 20 Exercises |
Jun 22 N-gram language models (1) [slides, 8up] Reading: JM Ch.4 |
| 10 | Jun 25 N-gram language models (2) |
Jun 27 A3 discussion, exercises [slides] |
Jun 29 POS tagging [slides, 8up] Reading: JM Ch.5 (JM3: Ch.10) |
| 11 | Jul 02 Statistical parsing (1) [slides, 8up] Reading: JM Ch.13 (JM3 Ch.12) |
Jul 04 A4 discussion, exercises [slides] |
Jul 06 Statistical parsing (2) |
| 12 | Jul 09 Vector representations (1) [slides, 8up] Reading: JM3 Ch.15&16 |
Jul 11 Exercises |
Jul 13 Vector representations (2) |
| 12 | Jul 16 Text classification [slides, 8up] |
Jul 18 A5 discussion, exercises [slides] |
Jul 20 NLP applications [slides, 8up] |
| 14 | Jul 23 Summary |
Jul 25 Exam |
Jul 27 Exam discussion & Wrap up |