Eigenvector and Eigenvalue Applications — Topic 34 of Machine Learning Foundations

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In this video, I provide real-world applications of eigenvectors and eigenvalues, with special mention of applications that are directly relevant to machine learning.

  1. Jon Krohn
  2. Matrix Determinants
  3. Eigenvalues
  4. Eigendecomposition
  5. Eigenvectors
  6. Linear Systems
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Комментарии
Автор

I listen to your data science podcast and have been going through your ML foundations course to solidify my mathematical foundations. Thank you for making this content, it's both a great review as well as a way to understand and interpret concepts such as eigenvectors and eigenvalues in new ways. Cheers!

ScilentE
Автор

Thank you sir. Yes COVID-19 is sort of in the rear view mirror but brings back memories every winter!

aamirsuleman
Автор

why for the vertical shear example both eigenvalues are equal to 2? if we take a matrix, say, [[1, 0], [2, 1]]. Numpy gives 2 values both equal to 1, and btw it shows 2 eigenvectors

sergeykurk
Автор

If an (n*n) matrix produces 'n' linearly independent eigenvectors with their eigenvalues, the horizontal shear transformation should have 2 linearly independent eigenvectors/eigenvalues, is that right?

electric_sand
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Is there a vídeo with more applications of eigen vectors?

Edu