CSCI 567
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CSCI-567 Schedule (fall 2008)

DateDescriptionChaptersSlidesComments
Aug 26 (NO CLASS) NO CLASS - Saved for presentations (Dec 2)      
Aug 28 Lecture 1
Overview/Introduction
1, 2.1 01-intro.pdf  
Sep 2 Lecture 2
Hypothesis spaces
2.7-2.10 02-hypothesis_spaces.pdf  
Sep 4 Lecture 3
Space of Algorithms
Linear Threshold Classifiers
2.7-2.10
10.1-10.4
03-space_of_algs_and_LTUs.pdf  
Sep 9 Lecture 4
Project details
Perceptrons
Logistic Regression
11.1-11.4
10.6-10.7
04-perceptrons_LogReg.pdf HW 1
Sep 11 Lecture 5
Linear Discriminant Analysis
6.6
5.1-5.5
05-LDA.pdf  
Sep 16 Lecture 6
Off-The-Shelf Learning Algorithms
Decision Trees
9.1-9.3 06-Off-The-Shelf-Algs-Decision-Trees.pdf  
Sep 18 Lecture 7
Decision Trees (cont)
  07-Decision-Trees.pdf HW 1 due
HW 2 posted
Sep 23 Lecture 8
Nearest Neighbor
8.1-8.5 08-Nearest-Neighbor.pdf Project pre-proposals due (1 page)
Sep 25 Lecture 9
Neural networks
11.5-11.7 09-10-Neural-Networks.pdf  
Sep 30 Lecture 10
Neural networks (cont)
    HW 2 due
HW 3 posted
Oct 2 (NO CLASS) No class - saved for presentations (Dec 4)      
Oct 7 Lecture 11
Bayesian Learning
Appendix A 11-12-Bayesian-Learning.pdf  
Oct 9 Lecture 12
Bayesian Learning (cont)
3.1-3.4, 3.7
4.4-4.51
  Project proposals due
Oct 14 Lecture 13
Support Vector Machines
10.9 13-14-SVM.pdf HW 3 due
Oct 16 Lecture 14
Support Vector Machines (cont)
     
Oct 21 MIDTERM      
Oct 23 Lecture 15
Learning Theory
2.2-2.3 15-16-learning-theory.pdf  
Oct 28 Lecture 16
Learning Theory (cont)
     
Oct 30 Lecture 17
Learning Theory finished
Bias/Variance Theory & Ensemble Methods
4.3
15.1-15.5
17-18-bias-variance.pdf HW 4 posted
Nov 4 Lecture 18
Bias/Variance Theory & Ensemble Methods (cont)
     
Nov 6 Lecture 19
Bias/Variance Theory & Ensemble Methods finished
Preventing Overfitting: Penalty and Hold-out methods
4.7-4.9 19-20-overfitting.pdf  
Nov 11 Lecture 20
Overfitting finished
Hold-Out and Cross-validation Methods
14.1-14.2   HW 4 due
Nov 13 Lecture 21
Penalty methods: decision trees, neural nets, SVMs
8.6-8.8 21-penalty-methods.pdf HW 5 posted
statlog.arff
statlog_test.arff
Nov 18 Lecture 22
Evaluating and Comparing Classifiers
14.3-14.9 22-evaluation-of-classifiers.pdf  
Nov 20 Lecture 23
Unsupervised Learning
7 23-24-unsupervised learning.pdf  
Nov 25 Lecture 24
Unsupervised Learning (cont)
7   HW 5 due
Nov 27Thanksgiving - No class      
Dec 2 (double class)
3:30-4:50pm GFS 118
5:00-6:20pm GFS 118
Lecture 25-26
Project Presentations 1 (double class)
    Project papers due
Dec 4 (double class)
3:30-4:50pm GFS 118
5:00-6:20pm GFS 118
Lecture 27-28
Project Presentations 2 (double class)
     
Dec 11 (GFS 118) FINAL: 4:30pm-6:30pm