What is backpropagation?

Updated May 17, 2026

Short answer

Backpropagation is an algorithm for computing gradients and updating weights in neural networks.

Deep explanation

It uses chain rule of calculus to compute gradients from output layer back to input layer, enabling optimization via gradient descent.

Real-world example

Used in training deep learning models like GPT and CNNs.

Common mistakes

  • Confusing backpropagation with gradient descent.

Follow-up questions

  • What is gradient descent?
  • Why is chain rule important?

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