Random Forests for Complete Beginners
I've started studying ML (as someone who's hoping to transition at 47 to a different career from teaching and music), and some concepts I've found easy to get, others not so much (I'm old, so give me a break!).  Often I need to have a concept explained in a different manner before I'll have a 'Oh, I see!' moment, and because I don't have a great grasp on the maths needed (which I'm working on, but it's s-l-o-w), as soon as equations I can't get appear, I tend to lose focus and think I can't do it.This post covers things that I've seen in the past, and seems to sum up my internal understanding of the concept, which is good for me as reading through it I had a number of 'see, I do get it' moments.  The only criticism I have of it is that it seems to gloss over what differences the trees within the random forest have - as I understand it, they are all slightly different, and this gives them greater accuracy?Anyway, thanks for posting it - I'll read the other posts when I get a chance.