Introduction to 10 601 Machine Learning Spring 2015 Recitation 9
If you are looking for information about 10 601 Machine Learning Spring 2015 Recitation 9, you have come to the right place. Topics: review of boosting, Adaboost, strong vs weak PAC
10 601 Machine Learning Spring 2015 Recitation 9 Comprehensive Overview
Topics: shattered sets, Vapnik–Chervonenkis (VC) dimension Lecturer: Maria-Florina Balcan ... Topics: support vector Topics: review of the solutions to midterm exam Lecturer: Travis Dick http://www.cs.cmu.edu/~ninamf/courses/601sp15/index.html.
10-601 Recitation
Summary & Highlights for 10 601 Machine Learning Spring 2015 Recitation 9
- Topics: high-level overview of
- Topics: EM algorithm, Gaussian mixture models, Chow-Liu algorithm Lecturer: Tom Mitchell ...
- Topics: bias-variance tradeoff, introduction to graphical models, conditional independence Lecturer: Tom Mitchell ...
- Topics: graph-based semi-supervised
- Topics: exam review, review of past exam questions Lecturer: Willie Neiswanger ...
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