Machine Learning, Deep Learning, Neural Networks, Heartbeat, Mlops.
idiosyncratic patterns in the training set, instead of generalizing to unseen data. Any modiﬁcation we make to a learning algorithm that’s intended to reduce its generalization error but not its training error is called regularization. Keeping the model simple enough by using regularization