Exploring 10 601 Machine Learning Spring 2015 Recitation 2
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- Topics: support vector
- Topics: exam review, review of past exam questions Lecturer: Willie Neiswanger ...
- Topics: EM algorithm, Gaussian mixture models, Chow-Liu algorithm Lecturer: Tom Mitchell ...
- Topics: graphical models, d-separation, Bayes' ball algorithm, inference Lecturer: Abu Saparov ...
- Topics: deep learning, restricted Boltzmann machines, privacy in
In-Depth Information on 10 601 Machine Learning Spring 2015 Recitation 2
Topics: Octave tutorial, Gaussian/normal distribution, maximum likelihood estimation (MLE), maximum a posteriori (MAP) Lecturer: ... Topics: decision trees, overfitting, probability theory Lecturers: Tom Mitchell and Maria-Florina Balcan ... Topics: high-level overview of Topics: review of naive Bayes, naive Bayes with Bernoulli, Gaussian, and multinomial (categorical) distributions Lecturer: Micol ...
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