58. Random Forest: Why One Tree Isn't Enough

You saw in the last post that decision trees overfit easily. Change a few training examples and the whole tree changes. That instability is the core problem. The fix is almost embarrassingly simple. Don't build one tree. Build hundreds of them. Make each one slightly different. Then have them all vote on the answer. That's Random Forest. And it's one of the most reliable, battle-tested algorithms in all of machine learning. What You'll Learn Here Why one tree fails and how combining many fixes i