Difference between revisions of "Syllabus for Machine Learning 10-601 in Fall 2013"
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| 9/11 || [[10-601 Perceptrons and Voted Perceptrons|The Perceptron algorithm]] || William | | 9/11 || [[10-601 Perceptrons and Voted Perceptrons|The Perceptron algorithm]] || William | ||
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Revision as of 15:31, 31 July 2013
This is the syllabus for Machine Learning 10-601 in Fall 2013.
Contents
Prezi Overview of All the Topics in the Course
Schedule
Date | Topic | Lecturer | Due assignment | New assignment |
---|---|---|---|---|
9/2 | No class - Labor day | |||
9/4 | Overview and Intro to Probability | William | ||
9/9 | The Naive Bayes algorithm | William | ||
9/11 | The Perceptron algorithm | William | ||
9/16 | Logistic Regression | William | ||
9/18 |
Section-by-Section
Linear Classifiers
A probabilistic view of linear classification:
Another view of classification:
- 10-601 Introduction to Linear Algebra
- 10-601 Perceptrons and Voted Perceptrons
- 10-601 Voted Perceptrons and Support Vector Machines
Summary: