Difference between revisions of "Syllabus for Machine Learning 10-601 in Fall 2013"
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| 9/2 || No class - Labor day || | | 9/2 || No class - Labor day || | ||
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− | | 9/4 || [[10-601 Introduction to Probability]] || William | + | | 9/4 || [[10-601 Introduction to Probability|Overview and Intro to Probability]] || William |
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− | | 9/9 || [[10-601 Naive Bayes]] || William | + | | 9/9 || [[10-601 Naive Bayes|The Naive Bayes algorithm]] || William |
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− | | 9/11 || [[10-601 Perceptrons and Voted Perceptrons]] || William | + | | 9/11 || [[10-601 Perceptrons and Voted Perceptrons|The Perceptron algorithm]] || William |
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Revision as of 15:28, 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 |
---|---|---|
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 |
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: