Support Vector Machine, Machine Learning, Artificial Intelligence, Data Science, Ambarish 224.
some expertise. SVMs are memory-intensive: The training of an SVM model requires a significant amount of memory and computational resources. This can be a problem when working with large datasets. Limited interpretability: the results produced by an SVM model can be hard to interpret, which can