Neural network

How it is used

The basic building block of deep learning. People describe a network by its architecture, its number of layers and its number of parameters. In conversation it is often just 'the network' or 'the net'.

Example sentences

1. We replaced the decision tree with a small neural network and gained four points of accuracy.

2. The neural network has twelve layers and about 80 million parameters.

Common collocations

• train a neural network
• deep neural network
• neural network architecture
• feedforward neural network

Related terms

• deep learningThe part of machine learning that uses neural networks with many layers. It powers modern speech recognition, image recognition and large language models.
• layerOne level of a neural network: a group of units that takes the output of the previous level, transforms it and passes the result on to the next one.
• weightsThe learned numbers on the connections of a neural network, which decide how strongly each input affects the next layer. Together they hold what the model has learned.
• activation functionA simple mathematical function applied to the output of each unit in a neural network. It adds non-linearity, which lets the network learn complex patterns.
• backpropagationThe method that calculates how much each weight in a neural network contributed to the error, by passing the error backward from the output layer toward the input.

This word in other fields

The same English word can have a different meaning in another field:

• neural network · Artificial Intelligence & Machine Learning

More terms: Machine Learning and Data Processing

• artificial intelligence
• machine learning
• model
• dataset
• training data
• label
• train
• supervised learning
• loss function
• overfitting
• test set
• accuracy