Steam-powered Turing Machine University of Washington Department of Computer Science & Engineering
CSE 546 - Machine Learning - Winter 2012
Mon, Wed 1:30-2:50 in EEB 003
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Instructor: Luke Zettlemoyer (lsz at cs dot washington dot edu)
Office hours: Tuesdays 11:00-12:00, CSE 658
TA: Lydia Chilton (hmslydia at cs dot washington dot edu)
Office hours: Mondays 3-4, CSE 5th floor lounge *NOTE DAY CHANGE*

Schedule [subject to change]

Week Dates Topics & Lecture Notes Readings
1 Jan 4 Introduction Bishop Ch. 1 (optional; mostly review)
2 Jan 9, 11 Decision Trees Mitchell, Ch. 3; Duda, Ch. 8; ID3 Paper
3 Jan 18 Ugh, snow... Snow, yeah!
4 Jan 23, 25 Point Estimation; Linear Regression Bishop 2.1-2.3.5;3.1-3.2
5 Jan 30, Feb 1 Naive Bayes; Logistic Regression; Perceptron Naive Bayes and Logistic Regression; Perceptron proofs(optional)
6 Feb 6, 8 Boosting, Clustering, EM Bishop 14.3; 9.1-9.4; Boosting Overview Paper
7 Feb 13, 15 EM (cont.); Instance Based Learning; Dimensionality Reduction Bishop 2.5; 12.1
8 Feb 22 PCA (see Dim Red slides), Support Vector Machine (SVMs) Bishop 7.1
9 Feb 27, 29 SVM Dual and Kernels (see SVM slides); Learning Theory Bishop 6.1-6.2
10 Mar 5, 7 Learning Thery (continues); Neural Networks Bishop 5.1-5.3




We will have 3-4 homework assignments, which will be listed below as they are assigned. Please submit your assignments to the online DropBox.

Final Mini-project

A final mini-project will completed during the last weeks of the term. See the full description. Please submit your code and writeup to the online DropBox.


The final grade will consist of homeworks (40%), a mid-term exam (25%), a final mini-project (30%), and course participation (5%).

Course Administration and Policies

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