At its core, a neural network is a system of algorithms that attempts to recognise underlying relationships in a set of data through a process that mimics the way the human brain operates.

Neural networks are inspired by our brain's structure. Just as we have neurons, these networks have artificial neurons or "nodes".

They consist of layers. The input layer (where data enters), one or more hidden layers, and the output layer (where we get the result).

They're computation-intensive, need lots of data, and their 'black box' nature can make results hard to interpret. But for now, they are are powerful tools letting machines approximate any function, detect patterns, and make predictions by mimicking some of the brain's processes.