Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of GraphSearch.
This lecture covers the diagonalization of symmetric matrices, the spectral theorem, and the use of spectral decomposition. It explains the process of finding eigenvalues and eigenvectors, the properties of symmetric matrices, and the conditions for diagonalizability. The lecture also discusses the concept of orthogonality and normalization in the context of symmetric matrices.