>"Nothing I learned in CS has an application to industry programming" is a regular complaint in discussion on education here and elsewhere. This is a good course to point to for people who have this very limited view on CS.
> Lecture 11 (Mon 5/2): Graphs as matrices and the Laplacian of a graph. Interpretations of the largest and smallest eigenvectors/eigenvalues of the Laplacian. Spectral embeddings, and an overview of applications (e.g. graph coloring, spectral clustering.)
What industry fields does this apply to? Machine Learning?
> Lecture 11 (Mon 5/2): Graphs as matrices and the Laplacian of a graph. Interpretations of the largest and smallest eigenvectors/eigenvalues of the Laplacian. Spectral embeddings, and an overview of applications (e.g. graph coloring, spectral clustering.)
What industry fields does this apply to? Machine Learning?