What is Dropout in Deep Learning? Do You Know What It Does?
Published in
6 min readJan 18, 2023
Dropout is a regularization technique for reducing overfitting in neural networks by randomly setting a fraction of input units to 0 at each update during training time, which helps prevent complex co-adaptations on training data. It is applied on the level of hidden units, rather than input features and can be used on any layer of the network. This way the model is forced to learn…
