Eigendecomposition Explained

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In this video, we explore how we can factorize a square matrix using the eigendecomposition and why this transformation can be useful when solving machine learning problems.

*References*
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*Contents*
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00:00 - Intro
00:25 - Eigenvectors and eigenvalues
01:31 - Eigendecomposition equations
03:36 - Matrix raised to a power
05:50 - Eigendecomposition of a symmetric matrix
07:12 - Outro

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#eigendecomposition #eigenvectors #eigenvalues #linearalgebra
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Thanks for making this video! This actually made sense to me

Kazshmir
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Wonderful collection of videos! Thank you very much

nicolascortegosovissio
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To use eigen decomposition method for finding A^p, we also need to find U and U^-1, which makes it a little bit lengthy . However it's usefull when p is very large.

varshak
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Interesting video, but it seems to focus on the application of decomposed matrices, instead of explaining how to actually perform such decompositions. The video appears to makes the assumption that the factorised quantities U and Λ are already known.

AntiProtonBoy
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Isn't this the same as diagonalization? We
find a basis of the eigenvectors of A, then find what A looks like in that basis.

AkiraTheCatgirl