STA D68H (Winter 2014): Advanced Machine Learning and Data Mining
- Lecture Schedule
Tentative Lecture Schedule
- Lecture 1 -- Machine Learning:
Introduction to Machine Learning, Probability Distributions
(notes
[pdf])
Reading: Bishop, Chapter 1:
sec. 1.1 - 1.3
- Lecture 2 -- Probability Distributions:
(notes
[pdf])
Reading: Bishop, Chapter 2:
sec. 2.1 - 2.4
- Lecture3 -- Regression
(notes
[pdf])
Reading: Bishop, Chapter 1:
sec. 1.5
Chapter 3: sec. 3.1 - 3.2
- Lecture 4 -- Bayesian inference
(notes
[pdf])
Reading: Bishop,
Chapter 3: sec. 3.3 - 3.5
- Lecture 5 -- Classification
(notes
[pdf])
Reading: Bishop,
Chapter 4: sec. 4.1 - 4.2
- Lecture 6 -- Classification II
(notes
[pdf])
Reading: Bishop,
Chapter 4: sec. 4.3 - 4.5
- Lecture 7 -- Gaussian Processes
(notes
[pdf])
Reading: Bishop,
Chapter 6: sec. 6.4
- Lecture 8 -- Mixture Models
(notes
[pdf])
Reading: Bishop,
Chapter 9: sec. 9.1 - 9.3.
- Lecture 9 -- Latent Variable Models
(notes
[pdf])
Reading: Bishop,
Chapter 12: sec. 12.1 - 12.2, 12.4
- Lecture 10 -- Modeling Sequential Data
(notes
[pdf])
Reading: Bishop,
Chapter 13: sec. 13.1 - 13.2.
- Lecture 11 -- Deep Learning Models
(notes
[pdf])
[
Home |
Course Information |
Assignments |
Lecture Schedule |
]
STA D68H (Winter 2014): Advanced Machine Learning and Data Mining
|| http://www.cs.toronto.edu/~rsalakhu/STAD68/
|