[iamnafets]

I've found Adele Cutler's presentation on random forests to be an outstanding resource for getting intuition of tree-based algorithms.

http://www.math.usu.edu/adele/RandomForests/UofU2013.pdf

Thinking about trees as a supervised recursive partitioning algorithm or a clustering algorithm is useful for problems that may not appear to be simple classification or regression problems.

[lackadaisicall]

I like this one better:

https://web.csulb.edu/~tebert/teaching/lectures/551/random_f...

I made it.

[claytonjy]

On the topic of complementary resources, I really like Ben Gorman's explanation: https://gormanalysis.com/random-forest-from-top-to-bottom/. His related posts on singular decisions trees and GBM's are just as good, too.