Principal Component, Machine Learning, Artificial Intelligence, Linear Algebra, Data Science.
n eigenvectors, all of which are orthogonal (and can be easily made orthonormal by dividing by the length of each vector), we can use the eigenvectors as a basis. Since our covariance matrix C is and always will be symmetric, the spectral theorem applies as well to our covariance matrix. We can