Machine Learning, Artificial Intelligence, Pca Analysis, Data Science, Support Vector Machine.
Support Vector Machines (SVMs), each explained in one line: Linear Kernel: It creates a linear decision boundary and works well for linearly separable data. Polynomial Kernel: It allows for non-linear decision boundaries and is useful when data has polynomial relationships. Radial Basis Function