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What is a neural network?
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Quick answer
A neural network is a computing system loosely inspired by the brain, made of layers of simple connected units that learn patterns from data. By adjusting the strength of connections during training, it can recognize images, understand speech, and power modern AI.
Key things to understand
- It's built from layers of simple units ('neurons') connected together.
- Each connection has a weight that strengthens or weakens a signal.
- Training adjusts those weights to reduce errors.
- It learns patterns from examples rather than being explicitly programmed.
- Deep networks (many layers) drive image, speech, and language AI.
People also ask
How does a neural network learn?
It makes predictions, measures the error, and adjusts its connection weights slightly to do better — repeating over many examples.
Is a neural network like a human brain?
Only loosely — it borrows the idea of connected 'neurons,' but it's far simpler and works through math, not biology.
What does 'deep learning' mean?
Using neural networks with many layers, which can learn very complex patterns — the basis of most modern AI.
Are neural networks like the human brain?
Loosely inspired by it, but far simpler and purely mathematical — they don't actually think or understand.
Part of the guide: How AI Works →