Learn PCA by building it with your own hands. Draw or generate data, center and standardize it, inspect the covariance matrix, watch eigenvectors emerge, and compare the raw data space directly against the standardized analysis space in one shared view.
Start by making a dataset that has some shape. PCA is only interesting when there is structure to explain.
Add points or load a preset to begin the tutorial.