What if$,$ instead of relying on a single deep decision tree, we harness the strength of an ensemble consisting of multiple shallower trees that combine their votes? This powerful technique is known as the "random forest," and it has been proven to outperform a standalone decision tree significantly. For the Random Forest, we'll use five small, shallow Decision Trees. Each tree is created using a subset of the features and data samples.