# What is Neural Network? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Neural Architectures  
> **Canonical Citation:** [https://spidits.com/ai-glossary/neural-network](https://spidits.com/ai-glossary/neural-network)

## Definition
An Artificial Neural Network (ANN) is a computing system inspired by the biological neural networks that constitute animal brains, structured as layers of interconnected nodes that process inputs to produce outputs.

## Architectural Mechanics & Deep Dive
An artificial neural network (ANN) is a computational model inspired by the biological structure of the human brain. It consists of layers of interconnected nodes (neurons): an input layer, one or more hidden layers, and an output layer. Each node has an associated weight and activation threshold. Neural networks learn by processing training data, calculating prediction errors, and using backpropagation to adjust weights to minimize errors.

## Industry Applications & Real-World Use Cases
Deep learning modeling, computer vision systems, and text generation frameworks.

## Frequently Asked Questions

### What are the main layers of a neural network?
The Input Layer, one or more Hidden Layers (which extract features), and the Output Layer (which generates classification or predictions).

### What makes a neural network non-linear?
The inclusion of activation functions in the hidden layers, which enables the network to learn complex mathematical equations.

## Related Terminology
- [deep-learning](https://spidits.com/ai-glossary/deep-learning)
- [activation-function](https://spidits.com/ai-glossary/activation-function)
- [backpropagation](https://spidits.com/ai-glossary/backpropagation)

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*From the SPIDITS AI Knowledge Base (336+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*