Edge Rewrite
restyle Source code View original
// HTMLRewriter · presentation

This page was redesigned at the edge.

Cloudflare fetched the original article and streamed it through HTMLRewriter to apply an entirely new visual system without rebuilding the source page.

Jump to content

Hidden layer

Edit links
From Wikipedia, the free encyclopedia
Example of hidden layers in a MLP

In artificial neural networks, a hidden layer is a layer of artificial neurons that is neither an input layer nor an output layer. The simplest examples appear in multilayer perceptrons (MLP), as illustrated in the diagram.[1]

An MLP without any hidden layer is essentially just a linear model. With hidden layers and activation functions, however, nonlinearity is introduced into the model.[1]

In typical machine learning practice, the weights and biases are initialized, then iteratively updated during training via backpropagation.[1]

References

[edit]
  1. 1 2 3 Zhang, Aston; Lipton, Zachary; Li, Mu; Smola, Alexander J. (2024). "5.1. Multilayer Perceptrons". Dive into deep learning. Cambridge New York Port Melbourne New Delhi Singapore: Cambridge University Press. ISBN 978-1-009-38943-3.


Retrieved from "https://en.wikipedia.org/w/index.php?title=Hidden_layer&oldid=1354276118"