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We perform PCA for both visualization and feature selection here.

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pca.py		pca.py
requirements.txt		requirements.txt

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principal-component-analysis-PCA

For details, see notebook. PCA is implemented with numpy and scipy to better understand PCA.

Sample data from MNIST dataset

Visualization of MNIST dataset after dimensionality reduction using PCA

Plot of variance explained by eigen values (to choose number of principal components)

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We perform PCA for both visualization and feature selection here.

visualization feature-selection pca eigenvectors principal-component-analysis eigenvalues explained-variance pca-with-numpy

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