Difference between revisions of "Syllabus for Machine Learning 10-601B in Spring 2016"
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''Teaching team: also see the [https://docs.google.com/spreadsheets/d/1CNT4I-nSFBxqNRt4wbXL8oVXkSnh_igVcq_gwhErfWo/edit#gid=0 Google Doc Spreadsheet]'' | ''Teaching team: also see the [https://docs.google.com/spreadsheets/d/1CNT4I-nSFBxqNRt4wbXL8oVXkSnh_igVcq_gwhErfWo/edit#gid=0 Google Doc Spreadsheet]'' | ||
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Revision as of 15:18, 6 January 2016
This is the syllabus for Machine Learning 10-601 in Spring 2016.
Schedule
In progress....
Teaching team: also see the Google Doc Spreadsheet
To other instructors: if you'd like to use any of the materials found here, you're absolutely welcome to do so, but please acknowledge their ultimate source somewhere.
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: