AI engineering glossary · Deep learning core
What is layer?
Layer: A group of neurons that process their inputs in parallel at the same depth of a network. Data flows from one layer to the next, and each layer transforms the representation produced by the previous one, typically into something more abstract.
Layer: an example
A small classifier might stack layers of 256, 128 and 10 neurons, each layer feeding the next.
Related terms
More Deep learning core terms
- Layer normalisation
- Leaky ReLU
- Learning rate finder
- LeCun initialisation
- Linear scaling rule
- Lion optimiser
- Log-sum-exp trick
- Logits
Where you learn it
Layer is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.