Support Vector Machines (SVM): SVM compute an optimal hyperplane dividing two classes, ensuring maximum margin between this boundary and the nearest samples. Kernels can be used to work with non-linearly separable datasets, and multiclass problems can be solved by combining binary classifiers [62]...