This short demo shows how to generate beautiful surface plots of implicite and explicite functions using default matlab routines. By adding some lighting and computing local surface normals we can produce renderings of unexpected quality.
In this note we will demonstrate the application of kernels for linear regression. We start exploiting the solution within a standard adjustment model in primary. We modify this approach transforming it to the dual form. Finally we introduce kernel notation and illustrate the advantages of this method for higher order regression.