Machine Learning, Artificial Intelligence, Deep Learning, Data Science, Mathematics.
maintaining a balance in the contribution of all features. This characteristic of L2 regularization is especially valuable when dealing with multicollinearity, as it helps in distributing the effect of correlated variables across multiple features, enhancing the model’s stability and performance.