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AI & Machine Learning · Intermediate

Dropout

A regularization technique that randomly deactivates a fraction of neurons during each training step.

Definition

Dropout prevents neurons from co-adapting and forces the network to learn redundant representations, reducing overfitting. It is active only during training; at inference all neurons are used. Typical rates are 0.1 to 0.5.

Example

tf.keras.layers.Dropout(0.2)

Exam tip

Dropout applies during training only, not inference.

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