Training

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MSE for regression, cross-entropy for classification, and the TD error loss in DQN — how loss functions guide neural network training.

Go to Loss Functions: Measuring How Wrong the Network Is →

The chain rule applied backwards through a neural network — computing gradients for every weight and verifying them with numerical finite differences.

Go to Backpropagation: Teaching Networks by Propagating Errors →