Using times the regularization parameter alpha , and the Kernel Ridge Regression which works similar to the Ridge Regression but with an addition of a kernel trick which allows to fit a non-linear function . The fourth ML model, a neural network, has been widely used in many classification and regression applications. Neural networks are built in layers, where each node in each layer is connected to all the nodes in the next layer. A mathematical loss function is dictating how much each node is contributing to the network, creating a complex structure that can predict values or classify objects .