For Random Forests, I like this one: https://www.gormanalysis.com/blog/random-forest-from-top-to-..., which also has a link to a decision-tree post. That blog also has the best GBM explainer I've seen yet (Gradient Boosted Machines are the _other_ tree-ensembling method in common use, where the trees are _stacked_ instead of _bagged_)
Your goal should not be to know enough to write an RF implementation, but rather to have some intuition behind how it works, so you can better choose when to use it or not. The likelihood of it ever making sense for you to write and RF algorithm for production use is extremely unlikely; use the great code that already exists for most languages.
For Random Forests, I like this one: https://www.gormanalysis.com/blog/random-forest-from-top-to-..., which also has a link to a decision-tree post. That blog also has the best GBM explainer I've seen yet (Gradient Boosted Machines are the _other_ tree-ensembling method in common use, where the trees are _stacked_ instead of _bagged_)
Your goal should not be to know enough to write an RF implementation, but rather to have some intuition behind how it works, so you can better choose when to use it or not. The likelihood of it ever making sense for you to write and RF algorithm for production use is extremely unlikely; use the great code that already exists for most languages.