During training, a special layer randomly turns off some of the connections in the network. What is this layer called, and what does it help prevent?

This layer is called Dropout. It helps prevent overfitting. Dropout works by randomly setting a fraction of the outputs of neurons in a layer to zero during each training step. When a neuron's output is set to zero, it means that neuron, along with its incoming and outgoing connections, is temporarily removed from the network for that particular training example. This random deactivation happens independently f....