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VisualizationsNeural Networks & How They Learn

Weight Regularization

Click to add a weight penalty to the loss. Large weights now cost extra, so the model must balance fitting the data against keeping its weights small.

fit error
3.20
weight penalty
1.49
=
total loss
3.20

Regularization adds a second term to the loss: a charge for having large weights. The model now has to balance fitting the data against keeping itself small.

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