Exploring 10 701 Machine Learning Fall 2014 Lecture 2
Exploring 10 701 Machine Learning Fall 2014 Lecture 2 reveals several interesting facts.
- Topics: perceptron, linear programming, "perceptron algorithm"
- Topics: course logistics, high-level overview of
- Topics: logistic regression, generative vs discriminative classifiers, analysis of perceptron algorithm Lecturers: Aarti Singh and ...
- Introduction to
- Topics: Practice working with probability distributions involving linear algebra and matrix calculus
In-Depth Information on 10 701 Machine Learning Fall 2014 Lecture 2
Topics: classification, naive Bayes, introduction to maximum likelihood estimation (MLE), and maximum a posteriori estimation ... Topics: overview of topics tested on exam, Q&A Topics: bag of words, maximum likelihood estimation (MLE), maximum a posteriori (MAP) Topics: overview of topics that may tested on exam, open Q&A
Topics: analysis of boosting, introduction to graphical models Lecturers: Aarti Singh and Geoff ...
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