Exploring 10 601 Machine Learning Spring 2015 Recitation 14
Exploring 10 601 Machine Learning Spring 2015 Recitation 14 reveals several interesting facts.
- Topics: boosting, weak vs strong PAC
- Topics: additional practice
- Topics: linear regression, logistic regression, gradient descent Lecturer: Kirstin Early ...
- Topics: support vector
- Topics: principal component analysis (PCA), dimensionality reduction, kernel PCA Lecturer: Ahmed Hefny ...
In-Depth Information on 10 601 Machine Learning Spring 2015 Recitation 14
Topics: exam review, review of past exam questions Lecturer: Willie Neiswanger ... Topics: EM algorithm, Gaussian mixture models, Chow-Liu algorithm Lecturer: Tom Mitchell ... Topics: inference in graphical models, expectation maximization (EM) Lecturer: Tom Mitchell ... Topics: Octave tutorial, Gaussian/normal distribution, maximum likelihood estimation (MLE), maximum a posteriori (MAP) Lecturer: ...
Topics: inference in graphical models, d-separation, conditional independence Lecturer: Tom Mitchell ...
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