Asked about Norms, projections and decompositions
How does PCA relate to eigenvectors?
An answer that works
PCA finds the eigenvectors of the data's covariance matrix. They are the directions of greatest variance, and the eigenvalues say how much variance each direction captures.
Reading an answer is not being able to give one. The section that teaches this is Norms, projections and decompositions, 5 hours of Linear algebra.
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