Understanding 10 701 Machine Learning Fall 2014 Midterm Review
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Key Takeaways about 10 701 Machine Learning Fall 2014 Midterm Review
- Machine Learning 10-701 Recitation 6 (Midterm review)
- Topics:
- Topics: kernel methods, kernel trick, intuition behind RKHS Lecturer: Adona Iosif ...
- Topics: clustering, hierarchical clustering methods, k-means, mixture of Gaussians Lecturer: Aarti Singh ...
- Topics: analysis of boosting, introduction to graphical models Lecturers: Aarti Singh and Geoff ...
Detailed Analysis of 10 701 Machine Learning Fall 2014 Midterm Review
Topics: overview of topics tested on Topics: course logistics, high-level overview of Topics: probabilistic modeling, graphical models, Gaussian mixture models, expectation maximization (EM) Lecturer: Abu ...
Topics: Practice working with probability distributions involving linear algebra and matrix calculus Lecturer: Anthony Platanios ...
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