Support Vector Machine, Machine Learning, Data Science, Deep Learning.
regularization parameter and the cost parameter. Fit the model: Once you’ve chosen the kernel and set the hyperparameters, you can fit the SVM model to the training data. This involves finding the optimal combination of weights and biases that allows the model to make accurate predictions on the