Introduction to Machine Learning

This talk is based on

• Tom M. Mitchell. Machine Learning. McGraw Hill. 1997. Chapter 1.
• and his slides.

1. 1 CSCE 883
2. 2 Outline
3. 3 Why Machine Learning
   1. 3.1 Bioinformatics Example
4. 4 Relevant Disciplines
5. 5 What is the Learning Problem?
   1. 5.1 Learning to Play Checkers
   2. 5.2 Learning Handwriting Recognition
6. 6 Choosing the Training Experience
7. 7 Choose the Target Function
   1. 7.1 Possible Definition for Target Function
8. 8 Choose Representation for Target Function
   1. 8.1 A Representation for the Target Function
9. 9 Training Examples
10. 10 Choose Weight Tuning Rule
11. 11 Final Design
12. 12 Design Choices
13. 13 Some Issues in Machine Learning

Entire Presentation with Notes

---

Copyright © 2009 José M. Vidal . All rights reserved.

15 January 2003, 04:48PM