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Early Stopping

Early stopping halts training when the validation loss stops improving, preventing overfitting and saving compute.

#early stopping#validation loss#patience+11
📚TheoryIntermediate

Dropout

Dropout randomly turns off (zeros) some neurons during training to prevent the network from memorizing the training data.

#dropout#inverted dropout
Intermediate
Advanced
Filtering by:
#overfitting
Group:
Regularization Theory
#bernoulli mask
+12
∑MathIntermediate

L2 Regularization (Ridge/Weight Decay)

L2 regularization (also called ridge or weight decay) adds a penalty proportional to the sum of squared weights to discourage large parameters.

#l2 regularization#ridge regression#weight decay+12