Why did deep networks stop learning?

Blame travels backward When a neural network makes a mistake, training works out how much each dial (each weight) was to blame. That blame starts at the answer and travels backward, layer by layer, so every dial knows which way to turn. This is backpropagation. On the way back, the blame passes through each layer's bend, the activation function.... Weiterlesen: Why did deep networks stop learning?