Support Vector Machine, Machine Learning, Artificial Intelligence, Data Science, Ambarish 224.
applications such as text classification and image classification. Ability to model nonlinear decision boundaries: Through the use of kernel functions, SVMs can model nonlinear decision boundaries. This makes them useful for problems where the data is non-linearly separable. Good generalization