Principal Component Analysis (PCA) from Scratch in Python
Principal Component Analysis, is one of the most useful dimensionality reduction techniques. In this video, I aim to explain how you can find out the n_components or number of principal components for a feature matrix by applying PCA from scratch and not using sklearn's PCA module.
This video is a simple walk-through of the amazing blog written by Sebastian Raschka!
Link to the Blog : https://sebastianraschka.com/Articles...
Principal component analysis is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components.
Link to the notebook : https://github.com/bhattbhavesh91/pca...
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