10-601B Perceptrons and Large Margin

This a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016

Slides

• Slides in powerpoint
• Slides in pdf

Useful Additional Readings

• The Perceptron Algorithm: Mitchell 4.4.1 & 4.1.2, Bishop 4.1.7
• Support Vector Machines: Bishop 7.1, Murphy 14.5

What You Should Know Afterward

• The difference between an on-line and batch algorithm.
• The perceptron algorithm.
• The importance of margins in machine learning.
• The definitions of, and intuitions behind, these concepts:
  • The margin of a classifier relative to a dataset.
  • What a constrained optimization problem is.
  • The SVM algorithm.
• How the perceptron and SVM are similar and different.