CSE 446 - Machine Learning

University of Washington Department of Computer Science & Engineering

CSE 446 - Machine Learning - Winter 2014
MWF 9:30-10:20am in Thomson Hall rm. 125

CSE Home

About Us

Contact Info

Instructor: Pedro Domingos (pedrod at cs)
Office hours: Mondays 10:30-11:20am
Office: Allen Center 648 TA: Robert Gens (rcg at cs)
Office hours: Wednesdays 4:00-5:00pm
Office: Allen Center 220 TA: Dimitrios Gklezakos (gklezd at cs)
Office hours: Thursdays 2:00-3:00pm
Office: Allen Center 220

Schedule

Week	Dates	Topics & Lecture Notes	Readings
1	January 6	Introduction (ppt, pdf), inductive learning (ppt, pdf)	Mitchell, Ch. 1; Duda, Ch. 1
2	January 13	Decision trees (ppt, pdf)	Mitchell, Ch. 3; Duda, Ch. 8
3	January 20	Rule induction (ppt, pdf)	Mitchell, Ch. 10; Duda, Ch. 8
4	January 27	Instance-based learning (ppt, pdf)	Mitchell, Ch. 8; Duda, Ch. 4
5	February 3	Bayesian learning (ppt, pdf)	Mitchell, Ch. 6; Duda, Ch. 2 & 3
6	February 10	Neural networks (ppt, pdf)	Mitchell, Ch. 4; Duda, Ch. 6
7	February 17	Model ensembles (ppt, pdf)	Duda, Ch. 9
8	February 24	Learning theory (ppt, pdf)	Mitchell, Ch. 7; Duda, Ch. 9
9	March 3	Support vector machines (ppt, pdf)	Duda, Ch. 5
10	March 10	Clustering and dimensionality reduction (ppt, pdf)	Duda, Ch. 10

Online Lectures

(Click on "Preview" to see the videos, and on the slides to make them larger.)

Textbooks

R. Duda, P. Hart & D. Stork, Pattern Classification (2nd ed.), Wiley, 2001 (required).
Tom Mitchell, Machine Learning, McGraw-Hill, 1997 (required).

Papers

P. Domingos, A Few Useful Things to Know about Machine Learning. Communications of the ACM, 55 (10), 78-87, 2012.
P. Domingos, A Unified Bias-Variance Decomposition and its Applications. Proc. 17th ICML, 231-238, 2000.

Assignments

There will be four assignments handed out on weeks 2, 4, 6, and 8; they are due two weeks later. Each assignment is worth 25% of the final grade. Submit online here.

Assignment 1: Clickstream Mining with Decision Trees, Rule Induction. Due January 31, 2014 at 9:30am. Dataset
Assignment 2: Collaborative Filtering and Bayes Nets. Due February 14, 2014 at 9:30am.
Assignment 3: Naive Bayes, Neural Nets, Ensemble Methods. Due February 28, 2014 at 9:30am. Main dataset for Naive Bayes | Original dataset for Extra Credit | Indices of emails used in the Main Dataset | Train & Test for bagging problem
Assignment 4: Learning Theory and SVMs. Due March 14, 2014 at 9:30am.

Course Administration and Policies

The course mailing list is cse446a_wi14@u.washington.edu (automatically populated).
Discuss course material on the forum.
Assignments will be done individually unless otherwise specified. You may discuss the subject matter with other students in the class, but all final answers must be your own work. You are expected to maintain the utmost level of academic integrity in the course.
Assignments may be handed in up to a week late, at a penalty of 10% of the maximum grade per day.
Comments can be sent to the instructor or TAs using this anonymous feedback form.

Department of Computer Science & Engineering
University of Washington
Box 352350
Seattle, WA 98195-2350
(206) 543-1695 voice, (206) 543-2969 FAX