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3_Eigendecomposition and PCA
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https://www.youtube.com/watch?v=-1iULsGndG8&list=PLn0OLiymPak1xJiggE5-ua5XoyDgxe1LG&index=3 Eigendecomposition is a technique that finds "special" vectors associated with square matrices. Eigendecomposition is the basis for many important techniques in data analysis, including principal components analyses, blind-source-separation, and other spatial filters. You'll also see a comparison between PCA and ICA. The video uses files you can download from https://github.com/mikexcohen/ANTS_youtube_videos For more online courses about programming, data analysis, linear algebra, and statistics, see http://sincxpress.com/
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