👉 In the context of machine learning, "regularizing" refers to techniques that help prevent overfitting or underfitting. In other words, it is a process by which models are trained using regularization to reduce their sensitivity to outliers and noise in data. Regularization can be done through various methods such as L1 (L2) regularization, Ridge regression, Huber loss function, etc. Regularizing helps prevent overfitting by making the model less sensitive to noise or irrelevant features. It
