10-601B Perceptrons and Large Margin
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Revision as of 22:36, 8 February 2016 by Tdick (talk | contribs) (Tdick moved page 10-601B Perceptrons and SVMs to 10-601B Perceptrons and Large Margin)
This a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016
Slides
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.
