CS 5751: Machine Learning

Lecturer: Rich Maclin (rmaclin)

Teaching Assistant: Hariprasad Bommaganti (hbommaga)

Syllabus

Grades

Class Materials:

• Textbook Web Page
• UCI Repository of ML Data Sets
• Chapter 1 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 2 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 3 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 4 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 5 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 8 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 9 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 10 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Clustering Review Read sections 1-5.7, 5.11-5.12 Clustering Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 13 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 11 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 12 Notes (PDF, 6 per page)   (PDF, 1 per page)
• Ensemble Paper   Ensemble Notes (PDF, 6 per page)   (PDF, 1 per page)
• Chapter 6 Notes (PDF, 6 per page)   (PDF, 1 per page)

Program Assignments:

1. Program 1
2. Program 2
3. Program 3 Revised files: train.C   alt3.2.data
4. Program 4
5. Program 5
6. Program 6

Team Assignments

Homework Assignments:

• Homework 1
• Homework 2
• Homework 3
• Homework 4
• Homework 5

Sample Exam Questions:

• Sample questions for Midterm 1
• Sample questions for Midterm 2

Take Home Final

C++ Notes (from 1622/1521) based on Learning C++: A Hands-On Approach by Nagler

• Intro to C++
• C++ Input and Output
• C++ Other Features
• C++ Classes

Useful web pages:

• Create a homepage
• A Beginner's Guide to HTML