Why does normalization improve gradient-based learning?

Updated May 16, 2026

Short answer

Normalization improves geometry of optimization space.

Deep explanation

Normalization ensures consistent scale across features and layers, preventing gradient explosion/vanishing and improving conditioning of Jacobian matrices.

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