Support Vector Machine, Machine Learning, Data Science, Deep Learning.
nonlinear classification and regression problems. Computational complexity: SVM can be computationally intensive, particularly when working with large datasets or when using a nonlinear kernel. This can make SVM less practical for some applications, compared to other algorithms that are faster to