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Classification and Regression Models in Machine Learning

Classification and Regression Models in Machine Learning, suitable for your ThinkRise study channel: Classification and Regression are two fundamental types of supervised learning models in machine learning. In this lesson, we break down how these models work, where they are used, and how to choose the right one for a given problem. You’ll understand the key difference between classification, which predicts categories or classes (such as spam vs. not spam or disease vs. healthy), and regression, which predicts continuous numerical values (such as house prices or temperature). This video covers popular algorithms like Linear Regression, Logistic Regression, Decision Trees, k-Nearest Neighbors (KNN), Support Vector Machines (SVM), and Random Forests, explained in a simple and intuitive way. We also discuss real-world applications, evaluation metrics, and common mistakes beginners make while building models.