Transforming a dataset into one with fewer columns is more complicated than it might seem, explains Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step machine learning tutorial.

You can think of eigenvalues and their associated eigenvectors as a decomposition of a matrix. Eigenvalues and eigenvectors are needed for PCA. But computing eigenvalues and eigenvectors directly is ...

Many quantum algorithms are developed to evaluate eigenvalues for Hermitian matrices. However, few practical approach exists for the eigenanalysis of non-Hermintian ones, such as arising from modern ...