Backpropagation
The algorithm used to compute gradients in neural networks, enabling efficient training through gradient descent.
In more detail
Backpropagation computes the derivative of the loss function with respect to each weight by chain rule, propagating errors backward through the network. This gradient is used to update weights in the direction that reduces loss. Fundamental to training deep neural networks.
Examples
- Training feedforward networks
- Training RNNs with BPTT
- Updating transformer weights
- Gradient-based optimization
Related terms
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