Backpropagation - AshokBhat/ml GitHub Wiki

About

• Primary algorithm for performing gradient descent on neural networks.

Process

• First, the output values of each node are calculated (and cached) in a forward pass.
• Then, the partial derivative of the error with respect to each parameter is calculated in a backward pass through the graph.

FAQ

• What is backpropagation?
• When it is used during training?

See also

• Gradient descent
• [Batch]] ](/AshokBhat/ml/wiki/[Batch-size) | [Mini-Batch]] | [Forward pass]] ](/AshokBhat/ml/wiki/[[Backpropagation)
• Chain rule