What is Dropout in AI?
Dropout is a regularization technique commonly used in deep
neural networks to prevent
overfitting. During training, Dropout randomly sets a fraction of the input units or weights to zero at each update, forcing the network to learn more robust and generalized representations. Dropout acts as a form of
ensemble learning, where multiple subnetworks are trained simultaneously.
