<human>:  Explain the concept of neural networks and how they work.
<bot>: Neural networks are computing systems loosely modeled after the hard wiring and neurons of the human brain. They are made up of interconnected artificial neurons that create a network that is able to process information in a manner similar to how biological brains work. Neural networks are commonly used in machine learning because of their ability to detect complex patterns in data and recognize relationships between input data and output responses. Generally, a neural network works by taking a set of inputs, passing them through a network of hidden layers, and then deriving a set of outputs. Each hidden layer is composed of nodes, analogous to the neurons in a biological brain, and each node is connected to many others in a highly specific manner. These weighted connections are then modified in response to input data, and the nodes are said to learn when the weights are continuously adjusted.