Machine Learning, Kernel, Hilbert Space, Mercer Theorem.
Historically, in Machine Learning, most of the underlying theory and algorithms developed were good in handling linearly separable data. However, modern data analysis problem requires methods capable of dealing with complex nonlinear data. To be able to handle such data, we need to map its features