Artificial Intelligence
What is A neural network?
A neural network is a computing system loosely inspired by the brain, built from layers of simple connected units ('neurons') that learn patterns from data. They power most modern AI, from image recognition to language models.
See it, don’t just read it.
Watch a 2-minute lesson with voice + animation that explains a neural network.
Key things to understand
- 1Each 'neuron' takes inputs, weights them, and passes a signal forward through layers.
- 2Training adjusts the weights so the network's outputs match the correct answers.
- 3'Deep' networks have many layers, letting them learn complex patterns.
- 4They underpin image recognition, speech, and large language models.
Frequently asked questions
- How does a neural network learn?
- It compares its output to the right answer and nudges its internal weights to reduce the error, repeating over many examples.
- What does 'deep learning' mean?
- Machine learning using neural networks with many layers, which can capture very complex patterns.
- Are neural networks like the human brain?
- Loosely inspired by it, but far simpler and purely mathematical — they don't actually think or understand.