SVM

We look at the use of kernel methods in machine learning and finance, highlighting their ability to transform complex, non-linear problems into solvable linear ones, thus revealing hidden patterns in data. Kernel methods, including Support Vector Machines and Radial Basis Function kernels, are widely applied in fields such as image and speech recognition, natural language processing, and bioinformatics, offering powerful tools for pattern analysis and prediction.