training
Regularization
Techniques used to prevent overfitting by adding constraints or penalties to the training process. Regularization encourages the model to learn simpler, more generalizable patterns rather than memorizing training data.
In practice
L2 regularization adds a penalty proportional to the square of weight values, discouraging any single weight from becoming too large.