Machine Learning & Training

What Is Dropout?

Dropout is a regularization technique for neural networks that randomly sets a fraction of neuron outputs to zero during each training step. This prevents the network from relying too heavily on specific neurons and encourages more robust, distributed representations. At inference time, all neurons are active and their outputs are scaled accordingly.