What is backpropagation in TensorFlow?

Updated May 16, 2026

Short answer

Backpropagation updates model weights using gradients.

Deep explanation

It computes gradients from output to input layers using chain rule.

Real-world example

Training deep neural networks.

Common mistakes

  • Not normalizing input data.

Follow-up questions

  • Why is gradient descent needed?

More TensorFlow interview questions

View all →