Perceptron
A perceptron is the simplest neural network — a single neuron that computes a weighted sum of inputs, adds a bias, and applies a step function. It is a linear binary classifier.
What is Perceptron?
A perceptron is the simplest neural network — a single neuron that computes a weighted sum of inputs, adds a bias, and applies a step function. It is a linear binary classifier.
A perceptron is the simplest neural network — a single neuron that computes a weighted sum of inputs, adds a bias, and applies a step function. It is a linear binary classifier.
Where is it used?
Perceptrons are the building blocks of all neural networks. Modern LLMs use the same weighted-sum-plus-activation pattern, just with millions of neurons stacked in layers.
How to build it
In PyTorch, create a single `nn.Linear` layer with one output, apply a sigmoid or threshold. Train it on 2D data with gradient descent using `torch.optim.SGD`.