What is Neural Network?
Neural Network — A computing system inspired by the biological neural networks that constitute animal brains.
Neural networks are composed of layers of interconnected nodes (neurons) that process data. Each connection has a weight that is adjusted during training. Deep neural networks with many layers can learn incredibly complex patterns in data — from recognizing faces to generating poetry.
Frequently Asked Questions
How does a neural network learn?
Through training. Data flows forward through the network producing a prediction. The error is calculated, then backpropagation adjusts connection weights to reduce future errors. This cycle repeats millions of times.
What types of neural networks exist?
CNNs for images, RNNs/LSTMs for sequences, Transformers for language, GANs for generation, and Graph Neural Networks for relational data. Each architecture is optimized for different data types.
Do I need to understand neural networks to use AI?
No. Modern AI tools and APIs abstract away the complexity. Understanding the concepts helps with selecting the right approach, but you do not need to build networks from scratch.