COMP-551-002: Topics in Computer Science: Applied Machine Learning

Schedule for Winter 2018

The course schedule is not finalized at this point, and subject change. Note that this is the schedule for section 002 only!

Lec.	Date	Topic	Lecture Material and Readings	Slides and Projects
1	Jan. 8	Introduction to machine learning.	Mandatory reading: This paper. Suggested readings: Bishop, Ch.1-2. Hastie et al., Ch.1. Shalev-Schwartz et al., Ch.2.	Slides
2	Jan. 10	Linear regression.	Suggested readings: Bishop, Ch.3. Hastie et al., Ch.2 (Sec.2.1-2.4, 2.9). Shalev-Schwartz et al., Ch.9	Slides
3	Jan. 15	Linear regression.	Suggested readings: Ch.3 (Sec.3.1-3.4, 3.9) of Hastie et al. Ch.3 of Bishop (Sec.3.1-3.2). Ch.5 and 11 of Shalev-Schwartz	Mini-project 1 will be released this week Slides
4	Jan. 17	Linear classification.	Suggested readings: Ch.4 of Hastie et al. Ch.4 of Bishop (Sec.4.1-4.3). Sec.9.3 of Shalev-Schwartz	First tutorial this Friday January 19th, 6-7 pm, Stewart Biology S3/3! Slides Project 1 instructions Data project 1
5	Jan. 22	Linear classification.	Suggested readings: Sec. 6.6.3 of Hastie et al. Ch.4 of Bishop (Sec.4.1-4.3). Sec.24.1-24.3 Shalev-Schwartz	Slides
6	Jan. 24	Performance analysis and error estimation.	Suggested readings: Ch.7 of Hastie et al. Wagstaff (2012) paper	Slides Mini-project 1 due on Jan. 26th29th at noon Mini-project 2 released on Jan 26th30th
7	Jan. 29	Instance-based learning	Suggested readings: Sec.2.5 of Bishop. Sec.13.3 of Hastie et al. Ch.19 of Shalev-Schwartz	Slides
8	Jan. 31	Support vector machines	Suggested readings: Ch.7 of Bishop. Ch.12 (Sec.12.1-12.4) of Hastie et al. Ch.15 of Shalev-Schwartz For more on convex optimization: see book by S. Boyd and L. Vandenberghe	Slides Project 2 instructions Project 2 data Second tutorial this Friday February 2nd, 6-7 pm, Stewart Biology S3/3! Notebook
9	Feb. 5	Support vector machines (cont'd)	Suggested readings: See lecture 9.	Slides
10	Feb. 7	Decision trees	Suggested readings: Sec.14.4 of Bishop. Sec.9.2 of Hastie et al.	Mini-project 2 due Feb. 7th12th at NOON. Slides
11	Feb. 12	Ensemble methods	Suggested readings: Sec.8.7, Ch.10 of Hastie et al. Ch.14 of Bishop Ch.10 of Shalev-Schwartz	Slides Mini-project 3 instructions Mini-project 3 data
12	Feb. 14	Ensemble learning, Feature design	Suggested readings: Ch. 3.1 of Bishop Ch. 8.8 of Hastie	Slides
13	Feb. 19	Feature construction and selection	Suggested readings: Ch. 12 of Bishop Ch. 14 of Hastie Ch. 23 of Shalev-Schwartz	Mini-project 3 due Feb. 19th23rd26th at NOON pm Slides
14	Feb. 21	Neural networks	Suggested readings Ch.11 of Hastie et al. Ch.5 of Bishop Ch.14 of Shalev-Schwartz Ch.6 of Goodfellow et al.	Slides
15	Feb. 26	Neural networks (cont'd)	Suggested readings: See lecture 14	Slides Project 4 instructions Project 4 Kaggle
16	Feb. 28	Deep learning	Suggested readings: Ch.9 of Goodfellow et al.	3rd tutorial (PyTorch) on March 2nd Slides
	March 5	Study week - no class
	March 7	Study week - no class
17	March 12	Deep learning (cont'd)	Suggested readings: Ch. 10 of Goodfellow et al.	Slides
18	March 14	Bayesian Inference	Suggested reading Bishop 1.2.3, 1.2.6, 2.3.6 Possibly Shalev-Scharz 24.5, Hastie 8.3	Slides
19	March 19	Bayesian Linear Regression and Bayesian Optimization	Suggested reading: Bishop 3.3, 6.4.1, 6.4.2 Rasmussen & Williams, chapter 2	Slides
20	March 21	Gaussian Processes	Suggested reading: Bishop 6.4.1, 6.4.2 Rasmussen & Williams, chapter 2	Project 4 due March 21st Slides
21	March 26	Unsupervised learning: Clustering	Suggested readings Ch. 9 of Bishop Ch. 14 of Hastier Ch.22. of Shalev-Schwartz	4th tutorial (Midterm Q&A) March 27th Slides Project 5 Instructions
22	March 28	Unsupervised learning: Clustering	Suggested readings Ch. 9 of Bishop Ch. 14 of Hastier Ch.22. of Shalev-Schwartz	Slides
	Apr. 2	Easter Monday - No class.
23	Apr. 4	No class. Midterm 5:30-8:30 pm (TBC) .
24	Apr. 9	Introduction to Reinforcement Learning		Slides
25	Apr. 11	Frontiers in machine learning		Slides
	Apr. 11	Final project presentation session, 1800-1930		Stewart Biology N2/2 (TBC)
26	Apr. 16	Final project presentation session		Final project due Apr. 20th
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