Date | Topic | Readings | Materials | |
Oct. 17 | Lecture | Introduction | Book, Chapter 1 | notes |
Oct. 19 | Tutorial | Background on probabilities | Chapters 1.2, (2.1-2.3) | notes |
Oct. 24 | Lecture | Linear regression | Chapter 3 | notes |
Oct. 26 | Tutorial | Numerical data processing in Python | notes | |
Oct. 31 | Lecture | Linear classification | Chapter 4 |
notes assignment 1 |
Nov. 2 | Tutorial | Questions about Assignment 1 and lecture | ||
Nov. 14 | Lecture | Non-linear models and back-propagation | Chapters 5.1-5.3, 5.5 | notes |
Nov. 16 | Tutorial | Discussion of Assignment 1 | solutions to programming exercises | |
Nov. 21 | Lecture | Clustering and the EM algorithm | Chapters 2.3.9, 9.1-9.4 |
notes assignment 2 |
Nov. 23 | Tutorial | Questions about Assignment 2 and lecture | ||
Nov. 28 | Lecture | Continuous latent variables and PCA | Chapters 12.1, 12.2, 12.4 |
notes |
Nov. 30 | Tutorial | Discussion of Assignment 2 | solutions to programming exercises | |
Dec. 5 | Lecture | Sequences and Hidden Markov Models |
Chapters 13.1, 13.2 Rabiner-Tutorial |
notes assignment 3 |
Dec. 7 | Tutorial | Questions about Assignment 1 and lecture | ||
Dec. 19 | Lecture | Graphical models | Chapter 8 |
notes |
Dec. 21 | Tutorial | Discussion of Assignment 3 | solutions to programming exercises | |
Jan. 9 | Lecture | Approximate inference and sampling | Chapters 10.1, 11.1-11.3 |
notes assignment 4 |
Jan. 11 | Tutorial | Questions about Assignment 4 and lecture | ||
Jan. 16 | Lecture | Overfitting, capacity control, Bayesian reasoning | Chapters 2.1, 2.2, 2.3, 3.3, 3.4, 3.5 |
notes |
Jan. 18 | Tutorial | Review | ||
Jan. 23 | Lecture |
Nonparametric methods, kernel methods, support vector machines |
Chapters 6, 7.1 |
notes |
Jan. 25 | Tutorial | Discussion of Assignment 4 | solutions to programming exercises | |
Jan. 30 | Lecture | Unsupervised feature learning and deep learning |
Useful (though very detailed) background reading includes: "Learning Deep Architectures for AI", Y. Bengio, 2009 or google: "deep unsupervised learning" |
notes |
Feb. 6 | Lecture | special lecture, not relevant for the exam | ||
Feb. 8 | Final exam |
Place: The usual Wednesday tutorial Room (SR307). Start: 2pm. Duration: 120 minutes. |