Artificial Intelligence 2: Machine Learning CSCI 4202

 

Course offered Spring 2005.

 

Location:          

Tuesday and Thursday 02:00pm-03:15pm in ECCR 133

Instructor:

Professor Greg Grudic

Office:            

ECOT 525

Office Hours:

Tuesday 3:30 to 4:30 PM

Thursday 10:00 to 11:00 AM

Phone:

303-492-4419

Email:

grudic@cs.colorado.edu

Course URL:

http://www.cs.colorado.edu/~grudic/teaching/CSCI4202_2005

 

Course Syllabus

 

 

Class Survey Survey.txt (email to me by end of week)

 

 

Grading:

    Project                                 50%

    Class Participation                10%

    Homework Assignments       40%

 

Homework:

·        Homework 1: Support Vector Machine Classification. (Assigned: Feb. 3, 2005. Due: Feb. 17 2005).   Data sets X_2_trn.txt, Y_2_trn.txt, X_2_val.txt, Y_2_val.txt, X_2_tst.txt.

·        Homework 2: The Ultimate Classifier (Assigned: March 3, 2005. Due: March 29, 2005).   Data sets X_2_trn.txt, Y_2_trn.txt, X_2_val.txt, Y_2_val.txt, X_2_tst.txt. Hints.

 

 

Lectures:

 

1.     January 11, 2005: Introduction

2.     January 13, 2005: Linear Separating Hyperplanes: Perceptron Algorithm (matlab code)

3.     January 18, 2005: Perceptron Algorithm, SVM Classification

4.     January 20, 2005: SVM Classification, Kernel Demo

5.     January 25, 2005: Model Selection

6.     January 27, 2005: Dimensionality Reduction: PCA and Kernel PCA. Students Discuss Class Project

7.     February 1, 2005: PCA and Kernel PCA demos. Student Projects.

8.      February 3, 2005: K-Means. Spectral Clustering. Related paper: Self-Tuning Spectral Clustering, Lihi Zelnik-Manor, Pietro Perona [ps.gz][pdf][bibtex]. Software available at http://www.vision.caltech.edu/lihi/Demos/SelfTuningClustering.html

9.     February 8, 2005: Projects. Evaluating Algorithms.

10.  February 10, 2005: Nearest Neighbor, Regression Introduction.

11.  February 15, 2005: Linear Regression, Ridge Regression, Lasso Regression, Nonlinear Regression, Kernel Ridge Regression.

12.  February 17, 2005: Support Vector Machine Regression. Student Projects.

13.  February 22, 2005: Discriminative Models and Generative Models for Classification.

14.  February 24, 2005: Neural Networks.

15.  March 1, 2005:  Neural Networks.

16.  March 3, 2005: Homework 2 Assigned. Students Discuss Class Project.

17.  March 8, 2005: Decision Trees. Students Discuss Class Project.

18.  March 10, 2005: Sparse vs. Ensemble.

19.  April 12, 2005: Notes.

20.  April 14, 2005: Bayesian Learning. Presentations.