Description

Backpropagation, short for "backward propagation of errors," is a widely used algorithm for training artificial neural networks. It efficiently computes the gradient of the loss function with respect to the weights of the network for a single input-output example, which is then used in optimization algorithms such as gradient descent to adjust the weights and minimize the loss.

Examples

• 🧠 Training multi-layer perceptrons
• 🖼️ Optimizing convolutional neural networks

Applications