Deep Learning
Backpropagation
Computing gradients by applying the chain rule in reverse topological order over the computation graph, caching intermediates.
Why interviewers ask about it
∂L/∂W = xᵀg needs the forward activation, which is exactly why activation memory dominates training and why gradient checkpointing exists.
Related terms
This term is part of the free AI/ML Engineer interview preparation module - browse the full glossary for every definition.