Machine Learning Fundamentals · Neural networks

Backpropagation

The algorithm that computes how much each weight in a neural network contributed to the error, so gradient descent knows which way to adjust it.

Also known as: backprop, chain rule for neural nets.

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Learn first

• Neural network basics: Stacking layers of logistic-regression-like units, connected by non-linear activation functions, to learn more complex patterns.

Related topics

• Hyperparameter tuning: Systematically searching for the settings (learning rate, regularization strength, tree depth) that aren't learned from data but chosen before training.