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3 results for “loss function”
Foundations
Backpropagation
Backpropagation is the primary algorithm for training neural networks, computing gradients of a loss function with respect to each weight by applying the chain rule of calculus in reverse through the network layers.
6 min readUpdated May 2026
Foundations
Cross-Entropy Loss
Cross-entropy loss is the standard objective function for training classification models, measuring the divergence between a predicted probability distribution and the true distribution of labels.
4 min readUpdated June 2026
Foundations
Gradient Descent
Gradient descent is an iterative optimisation algorithm that minimises a loss function by repeatedly updating model parameters in the direction of the steepest descent, as defined by the negative gradient.
6 min readUpdated May 2026