Machine Learning, Linear Algebra, Mathematics, Eigenvectors, Matrix.
useful, let’s first understand the underlying properties when a matrix is symmetric. If a matrix is symmetric, the eigenvalues are REAL (not COMPLEX numbers) and the eigenvectors could be made perpendicular (orthogonal to each other). Why do we have such properties when a matrix is symmetric? Let’s