Chapter
Understanding Backpropagation in Neural Networks
1:13:06 - 1:19:34 (06:27)
Backpropagation is the process of using error signals from the output layer to adjust the weights of connections in earlier layers of a neural network. This technique allows for more accurate predictions and has been used to train multi-layer neural networks.
Clips
Backpropagation is a technique used in neural networks to adjust the weights of the input-hidden layer connections.
1:13:06 - 1:19:34 (06:27)
Neural Networks
Summary
Backpropagation is a technique used in neural networks to adjust the weights of the input-hidden layer connections. Gradient descent is used with multiple neuron-like processing units and for single layers of connection weights.