The first seven algorithms could be defended as "elementary" methods that would help someone work up to neural nets and deep learning. But once he starts talking about SVM, I think he's talking of a method as sophisticated as neural nets and deep learning.

Neural nets and SVM were competitors - competitively applicable and competitively difficult - in the aughts. Deep learning has now pulled away but not by the discovery of fundamentally more complicated methods. Rather, the process has involved lot and lots and lots of little refinements, through throwing lots of people, advanced-math intuitions and computing power at it, etc. Learning everything needed to create state-of-the-art results is hard (as far I can tell/guess) but the basics are reasonably simple.