Unit 2.4.1 Principle Component Analysis (PCA)
Principle Component Analysis (PCA) is a standard technique in data science related to the SVD. You may enjoy the article
 J. Novembre, T. Johnson, K. Bryc, Z. Kutalik, A.R. Boyko, A. Auton, A. Indap, K.S. King, S. Bergmann, M.. Nelson, M. Stephens, C.D. Bustamante, , Nature, 2008.
In that article, PCA is cast as an eigenvalue problem rather than a singular value problem. Later in the course, in Week 11, we will link these.