Glossary · Phase 4 · Deep learning
Linearly separable
When one straight line (or flat surface) can split the yes examples from the no examples. A single neuron can only learn these.
Try it now
Multiply each input by its weight, add the bias, then pass the sum through an activation. Move anything and follow the numbers.
Learn it properly
The artificial neuron · Weighted sum plus a nonlinearity. About 25 minutes.
Other terms from the same lesson
- hyperplane: A flat dividing surface in any number of dimensions: a line in 2D, a flat sheet in 3D, and so on.
- neuron: One unit in a neural network: a weighted sum of its inputs, then a simple function.
- XOR: "Exclusive or": yes when exactly one of two things is true, but not both. One neuron can't learn it; two layers can.
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