A Neural Network is a computational model inspired by the structure and functioning of the human brain. It consists of interconnected nodes, or artificial neurons, organized into layers. In a typical neural network, there are three types of layers: the input layer, one or more hidden layers, and the output layer. Each connection between neurons is associated with a weight, and each neuron has an activation function that determines its output based on the weighted sum of its inputs. Neural networks are used in machine learning to learn patterns and relationships in data, and they can be applied to various tasks such as classification, regression, pattern recognition, and more. Deep Neural Networks (DNNs) refer to neural networks with multiple hidden layers, and they have been particularly successful in capturing complex features and representations from data.

Note: This concise definition provides an overview of Neural Network. For further information, a more in-depth search on Google is recommended.