Difference between revisions of "Syllabus for Machine Learning 10-601 in Fall 2013"
From Cohen Courses
Jump to navigationJump to search| Line 7: | Line 7: | ||
=== Linear Classifiers === | === Linear Classifiers === | ||
| + | A probabilistic view of linear classification: | ||
* [[10-601 Introduction to Probability]] | * [[10-601 Introduction to Probability]] | ||
* [[10-601 Naive Bayes]] | * [[10-601 Naive Bayes]] | ||
* [[10-601 Logistic Regression]] | * [[10-601 Logistic Regression]] | ||
| + | |||
| + | Another view of classification: | ||
* [[10-601 Introduction to Linear Algebra]] | * [[10-601 Introduction to Linear Algebra]] | ||
* [[10-601 Perceptrons and Voted Perceptrons]] | * [[10-601 Perceptrons and Voted Perceptrons]] | ||
* [[10-601 Voted Perceptrons and Support Vector Machines]] | * [[10-601 Voted Perceptrons and Support Vector Machines]] | ||
| + | |||
| + | Summary: | ||
| + | * [[10-601 Wrap-up on Linear Classification]] | ||
Revision as of 10:09, 3 July 2013
Prezi Overview of All the Topics in the Course
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:
