Why do random forests work? They are self-regularizing adaptive smoothers

Any suggestions for a 101 introduction to random forests? In university I encountered some ML courses but never random forests.

Yeah I did a deep dive on them here -- doesn't require any particular math background beyond high school: https://www.youtube.com/watch?v=blyXCk4sgEg

Statquest is really good. Maybe a little basic if you’ve taken ML courses, though?

https://youtube.com/playlist?list=PLblh5JKOoLUIE96dI3U7oxHaC...

Grab any ML book and read the chapter on random forests. If you have the maths background (which is not particularly high for random forests) which you should if you took ML courses, it’s all going to be pretty straightforward. I think someone already mentioned Hastie, The Elements of Statistical Learning, in this thread which you can download for free and would be a good start.

My book, Effective XGBoost, covers tree theory from stumps to decision trees, to bagging (random forests) to boosting.