Neural Network
A neural network is a machine learning model structure loosely inspired by the human brain, made of layers of connected nodes that learn to recognize patterns in data.
How Neural Network works
A neural network passes data through layers of simple mathematical units ("neurons"), each adjusting how strongly it reacts to different patterns. Through training on many examples, the network gradually tunes these connections to recognize increasingly complex patterns — from edges in an image to entire objects, or from words to meaning and context.
Why it matters for your business
You'll rarely need to build a neural network yourself, but the term appears constantly in vendor pitches and AI training materials. Knowing it's simply "the pattern-recognition engine under the hood" helps you cut through jargon when evaluating AI products.
Frequently Asked Questions
Do I need to understand neural networks to use AI tools?
No. Just like you don't need to understand a car engine to drive, most business users of AI tools never touch the underlying neural network — it's handled by the platform.
Are neural networks and deep learning the same thing?
Deep learning refers to neural networks with many layers. All deep learning uses neural networks, but not every neural network is 'deep.'