Differences between Decision tree & Random forest? Learn fast by example (Python)

In this tutorial, learn the difference within Random forest & Decision tree clearly with example in Python. Decision tree & Random forest algorithm are used in both classification & regression problem. A decision tree is built on an entire dataset, using all the features, while a random forest randomly selects observations and features to build multiple decision trees. They are different in terms of decision for final output, performance, computation time, overfitting & applicability. Jump in the video to find more!