04 Singular Value Decomposition
In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix that generalizes the eigendecomposition of a square normal matrix to any {\displaystyle m\times n} matrix via an extension of the polar decomposition.

Below is the demo in English, हिंदी (Hindi), తెలుగు(Telugu)

English

हिंदी (Hindi)

తెలుగు (Telugu)

reduction: https://en.wikipedia.org/wiki/Gaussian_elimination

Example : https://www.d.umn.edu/~mhampton/m4326svd_example.pdf

Social Media:

https://www.linkedin.com/in/meeraj-k-69ba76189/

https://facebook.com/meeraj.k.35

https://www.instagram.com/meeraj.kanaparthi1/

https://twitter.com/MeerajKanapart1
['Meeraj Kanaparthi']
['Datascience Training', 'Videos', 'Machine Learning', 'Svd', 'Jupyter Notebook']