# Gradient Flow

> Source: https://sukruyusufkaya.com/en/glossary/gradient-flow
> Updated: 2026-05-13T19:59:50.317Z
> Type: glossary
> Category: derin-ogrenme
**TLDR:** A core training-dynamics concept describing how effectively the learning signal moves across network layers.

<p>Gradient flow is a critical concept for understanding how well learning signals reach different layers in a deep network. If gradients become too small, early layers fail to learn; if they become too large, training becomes unstable. For this reason, activation functions, normalization layers, residual connections, and initialization strategies all directly influence gradient flow. Successful deep learning engineering depends heavily on maintaining healthy gradient dynamics.</p>