Beginner · Neural Networks
Depth
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. The total number of hidden, output, and embedding layers in a neural network.
Technical Definition
The total number of hidden, output, and embedding layers in a neural network.
How it works
In the context of neural networks, depth refers to the total count of layers, excluding the input layer. Specifically, it includes all hidden layers, any embedding layers, and the final output layer. A network with more layers is considered deeper and can potentially learn more intricate patterns.
Related Concepts
- Neural Network — A computing system inspired by biological neural networks that learns patterns from data through interconnected layers of nodes.
- Deep Learning — A subset of machine learning using neural networks with many layers to learn hierarchical representations from large datasets.
- Layer — A group of neurons that perform the same kind of transformation in parallel.
- Hidden Layer — Any layer in a neural network that is neither the input nor the output.