Interactive explorer: geometry, anatomy, learning rule, and XOR limitation
The perceptron draws a line in input space. Points on one side → class 1, other side → class 0. Drag the sliders to rotate and shift the boundary.
The weight vector w = (w₁, w₂) is drawn in orange — it is always perpendicular to the decision boundary. This is the key geometric fact.
Click any part of the diagram to learn more.
Watch the perceptron learn. It makes a prediction, checks if it's wrong, then nudges its boundary toward the mistake.
XOR cannot be solved by any single straight line — the perceptron's fundamental limitation.
The fix: stack two perceptrons → hidden layer → the network can learn non-linear boundaries. That is the leap from a single perceptron to a neural network.