Introduction to Machine Learning

This talk is based on

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