Support Vector Machines

Support vector machines (SVMs) are a powerful classification algorithm that can be used for linear and non-linear problems. SVMs work by finding the optimal hyperplane that separates the data into different classes with the maximum margin. They can be extended to non-linear problems using the kernel trick, which allows the algorithm to learn more complex decision boundaries.