Neural Network

What Is Neural Network?

A neural network is a computational structure inspired by how brains process information. It consists of layers of nodes (called neurons or units) connected by weighted edges. Information flows through these layers, with each neuron performing simple mathematical operations and passing results forward. The power emerges from millions of these simple operations working together.

Neural networks learn through a process called backpropagation, where the model makes predictions, measures how wrong it was, and adjusts the weights to reduce future errors. This iterative process, repeated over thousands or millions of examples, allows neural networks to learn complex patterns in data that traditional algorithms cannot capture.

Different network architectures serve different purposes: convolutional neural networks excel at image recognition, recurrent neural networks handle sequential data like text and time series, and transformer networks (used in modern LLMs) process information in parallel and understand context relationships effectively. Neural networks power most modern AI applications.