AI GlossaryNeuronENTRY — Neural Networks
[Neural Networks]
Neuron.
A basic computational unit in a neural network that receives inputs, applies weights and activation, and produces output.
In-depth explanation
01A neuron (or node) receives inputs from other neurons or external sources, multiplies each by a weight, sums them with a bias term, and applies an activation function to produce output. Neurons are organized into layers, and the collective behavior of many neurons enables neural networks to learn complex patterns.
Examples
02EX. 01
Perceptron
EX. 02
Sigmoid neuron
EX. 03
ReLU neuron
More in Neural Networks
0301Activation FunctionA mathematical function that determines the output of a neuron based on its weighted input sum.02BackpropagationThe algorithm for calculating gradients of the loss function with respect to network weights.03Batch SizeThe number of training examples used in one iteration of model training.04EpochOne complete pass through the entire training dataset during model training.05Neural NetworkA computing system inspired by biological neural networks, consisting of interconnected nodes (neurons).
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