Classification Trees (1/4) | Visually Explained | Machine Learning

Decision trees are one of the most intuitive models in machine learning, but understanding how they actually work can still be tricky. In this video, you will see a fully visual explanation of decision trees. We walk through how a tree makes predictions, how it splits the input space into regions, and how these regions correspond to final decisions. Instead of focusing on formulas, the goal is to build intuition. You will see how a single data point moves through the tree, how each question reduces the space, and how the model ultimately classifies the data. This is also the foundation for more advanced models like random forests and gradient boosting, which are widely used in data science, artificial intelligence, and engineering applications. In the next step, we will look at how decision trees are trained from data, how splits are chosen, and how to avoid overfitting. #MachineLearning #DecisionTree #ArtificialIntelligence #DataScience #AI #RandomForest #DeepLearning #Engineering #DataAnalysis #ML #TechExplained #LearnAI #Statistics #Coding #Python