In this Python ML project, we will explore an individual DecisionTree and learn to use pre-pruning and post-pruning techniques. Prepruning techniques are generally easier to use and involve setting hyperparameters that limit the growth of our decision trees. Post-pruning techniques are a little harder to work with but very important to understand how to use the when applying them to a random forest of decision trees. Let's practice with pre and post-pruning techniques in Sklearn in this Python Machine Learning Project.