Bhavesh Bhatt

Bhavesh Bhatt

GitHub Star ⭐ | Google Develeoper Expert in ML | 40 under 40 Data Scientist

Principal Component Analysis (PCA) from Scratch in Python

Principal Component Analysis, is one of the most useful dimensionality reduction techniques. It 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.

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.

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