Machine Learning, Artificial Intelligence, Deep Learning, Data Science, Mathematics.
ensuring that the model remains versatile and performs consistently across various datasets. Regularization achieves this by imposing constraints on the model during the training process. These constraints prevent the model from becoming overly complex and intricate, which is often the root cause