this is matlab pca code by me this is for you

PCA-master
..........\README.md
..........\basics
..........\......\README.md
..........\......\angle-removed.png
..........\......\angle-removedx.png
..........\......\angle-removedy.png
..........\......\edited-drop-to-x.png
..........\......\edited-drop-to-y.png
..........\......\edited-random-to-normal.png
..........\......\gaussDist-labeled.png
..........\......\normalized-angle-removed.png
..........\......\normalized-centered.png
..........\......\pca-gaussian.png
..........\......\random-gaussian.png
..........\......\randomness.py
..........\......\removedx.png
..........\......\removedy.png
..........\digitIdentification
..........\...................\README.md
..........\...................\covaraince-[ca-matpotlib.png
..........\...................\covariance-pca.png
..........\...................\digitid.py
..........\...................\pca-difference.png
..........\...................\pca-digit-0.png
..........\...................\t10k-images-idx3-ubyte
..........\...................\t10k-labels-idx1-ubyte
..........\...................\train-images-idx3-ubyte
..........\...................\train-labels-idx1-ubyte
..........\digitPCA
..........\........\PCA.gif
..........\........\README.md
..........\........\digit-pca.png
..........\........\digit.m
..........\........\pca-nmf.png
..........\digitRec
..........\........\digit-pca.png
..........\........\digit.m
..........\........\digits.mat
..........\seedAnalysis
..........\............\README.md
..........\............\eigenvalues.png
..........\............\eigenvalues2.png
..........\............\first-two-principle-components.png
..........\............\seedAnalysis.m
..........\............\seedAnalysis.py
..........\............\seedPCAComp.gif
..........\............\seedRegComp.gif
..........\............\seeds_dataset.csv
..........\............\seeds_dataset.txt

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