Machine Learning
CSCI 5622 Section 001
Location: 
Tuesday and Thursday
9:3010:45 ECCR 1B08 
Instructor:

Professor
Greg Grudic 
Office: 
ECOT
525 
Office
Hours: 
Tuesday and Thursday 11:0012:30 
Phone: 
3034924419 
Email:

grudic@cs.colorado.edu 
Course
URL: 
Grading:
Homework 50%
Project 25%
Class Participation 5%
Final 20%
Textbook: Machine Learning by
Tom Mitchell.
Goals: Understand the theory and practice of the most commonly used Machine Learning Algorithms. After taking the course you will be able to 1) read current research papers in machine learning and 2) understand the relevant issues addressed by these papers. In other words, you should be able to do basic (relevant) research in machine learning after taking this course.
Lecture Schedule
Aug 28 Introduction
Aug 30 Nearest neighbor [Chapter 8.18.3]
Sep 04 Probabilistic networks: Naive Bayes [Section 6.96.11]
Sep 06 Hypothesis Evaluation [Chapter 5}  HW1 assigned
Sep 11 Decision Trees C4.5 [Chapter 3.13.6, 3.7.2]
Sep 13 Decision Trees (Finish)
Sep 18 PAC Learning [Chapter 7.17.3]
Sep 20 PAC Learning with continuous parameters [Chapter 7.4]  HW1 due, HW2 assigned
Sep 25 Simple Neural Networks I [Chapter 4.14.4]
Sep 27 Simple Neural Networks II
Oct 02 Multilayer Neural Networks [Chapter 4.54.7]
Oct 04 FALL BREAK
Oct 09 Neural Networks – tricks and variations [Chapter 4.8]  HW2 due, HW3 assigned
Oct 11 Neural Networks – tricks and variations [Chapter 6.5; 8.4; 12.312.4]
Oct 16 Bayesian Learning Theory [Chapter 6.16.8]
Oct 18 Rate of Convergence and Computational Complexity properties.
Oct 23 Support Vector Machines
Oct 25 Support Vector Machines
Oct 30 Bias – Variance Theory (Bagging)  HW3 due, HW4 assigned
Nov 01 Bias – Variance Theory (Boosting) – Selection of Final Project
Nov 06 Unsupervised Learning I  HW4 due
Nov 08 Unsupervised Learning II
Nov 13 Reinforcement Learning I Ch 13
Nov 15 Reinforcement Learning II
Nov 20 Genetic Algorithms
Nov 22 THANKSGIVING
Nov 27 Review I
Nov 29 Review II
Dec 04 NIPS
Dec 06 NIPS
Dec 11 Presentation of Final Projects
Dec 13 Presentation of Final Projects