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Lecture 09, part 1 | Pattern Recognition

This lecture by Prof. Fred Hamprecht covers dimensionality scaling and stochastic neighbor embedding. This part introduces dimensionality reduction methods, multidimensional scaling, Sammon's NLM and isomap. This lecture is part of a course on Pattern Recognition by Prof. Fred Hamprecht from the Physics department of Heidelberg University. The course introduces modern machine learning methods with an eye to applications in image analysis.

Tags: eigenmap, embedding, kernel, learning, math, multidimensionality, neighbor, pattern, scaling, science, stochastic
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