Data Science, Linear Algebra, Machine Learning.
input features and target variables. Kernel methods in linear algebra are a powerful tool for working with data in high-dimensional spaces without explicitly calculating those dimensions. They are particularly useful when dealing with nonlinear relationships between data points and have