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: linear regression, logistic regression, gradient descent Lecturer: Kirstin Early ...
- Topics: review of naive Bayes, naive Bayes with Bernoulli, Gaussian, and multinomial (categorical) distributions Lecturer: Micol ...
- Topics: graph-based semi-supervised
- Topics: additional practice
- Topics: graphical models, d-separation, Bayes' ball algorithm, inference Lecturer: Abu Saparov ...
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