AI engineering glossary · Deep learning core
What is group normalisation?
Group normalisation: A normalisation that splits a layer's channels into groups and standardises within each group for every example separately. It does not rely on batch size, so it works well when memory limits force very small batches.
Group normalisation: an example
With 32 channels in 8 groups, each normalisation covers 4 channels of one image.
Related terms
More Deep learning core terms
Where you learn it
Group normalisation is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.