Medium Last updated on May 7, 2022, 1:06 a.m.
Dropout is a method used by Neural Networks to avoid Overfitting. In simple terms, During training a Neural Networks, we randomly choose certain neurons and set them to zero (ignore) for forward pass or backward pass.
These neurons are chosen by a probability p, i.e; individual nodes are kept with probability (1-p) so that a reduced network is left; incoming and outgoing edges to a dropped-out node are also removed.
Inverted Dropout Method is commonly used for Drop out Implementation