Exploring 10 601 Machine Learning Spring 2015 Recitation 8
Exploring 10 601 Machine Learning Spring 2015 Recitation 8 reveals several interesting facts.
- Topics:
- Topics: additional practice
- Topics: Octave tutorial, Gaussian/normal distribution, maximum likelihood estimation (MLE), maximum a posteriori (MAP) Lecturer: ...
- Topics: graphical models, d-separation, Bayes' ball algorithm, inference Lecturer: Abu Saparov ...
- Topics: generative and discriminative classifiers (relationship between naive Bayes and logistic regression), linear regression ...
In-Depth Information on 10 601 Machine Learning Spring 2015 Recitation 8
Topics: review of the solutions to midterm exam Lecturer: Travis Dick http://www.cs.cmu.edu/~ninamf/courses/601sp15/index.html. Topics: introduction to computational Topics: support vector Topics: review of naive Bayes, naive Bayes with Bernoulli, Gaussian, and multinomial (categorical) distributions Lecturer: Micol ...
Topics: Logistic regression and its relation to naive Bayes, gradient descent Lecturer: Tom Mitchell ...
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