Backpropagation
An algorithm for training artificial neural networks based on calculating gradients of the loss function.
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
🤖 Deep learning model training
🔧 Error correction in neural networks
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