Support Vector Machines (SVMs) are a type of supervised machine learning algorithm used primarily for classification and regression tasks. They work by finding the hyperplane that best separates different classes in the training data. The hyperplane is chosen to maximize the margin between the classes, ensuring robust classification or prediction.
