Exploring 10 601 Machine Learning Spring 2015 Recitation 4
Welcome to our comprehensive guide on 10 601 Machine Learning Spring 2015 Recitation 4.
- Topics: review of the solutions to midterm exam Lecturer: Travis Dick http://www.cs.cmu.edu/~ninamf/courses/601sp15/index.html.
- Topics: inference in graphical models, expectation maximization (EM) Lecturer: Tom Mitchell ...
- Topics: wrap-up of semi-supervised
- Topics: introduction to computational
- Topics: reinforcement
In-Depth Information on 10 601 Machine Learning Spring 2015 Recitation 4
Topics: linear regression, logistic regression, gradient descent Lecturer: Kirstin Early ... Topics: conditional independence and naive Bayes Lecturer: Tom Mitchell ... Topics: Topics: high-level overview of
Topics: review of boosting, Adaboost, strong vs weak PAC
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