A neural network is a computational model inspired by the structure and function of the human brain's biological neural networks. It consists of layers of interconnected units called artificial neurons or nodes, which process data and make decisions in a way that mimics how neurons in the brain work together

. Key characteristics of a neural network:

• Structure: It has an input layer that receives data, one or more hidden layers that transform the data, and an output layer that produces the final result

• Neurons: Each neuron receives inputs, applies a mathematical operation (often a weighted sum followed by a nonlinear activation function), and passes the output to neurons in the next layer

• Learning: Neural networks learn by adjusting the weights and biases of connections between neurons based on training data. This process often involves backpropagation and optimization techniques like gradient descent to minimize errors

• Function: They are capable of recognizing patterns, making predictions, and solving complex problems such as image and speech recognition, natural language processing, and more

Neural networks are a fundamental part of machine learning and deep learning, enabling computers to model complex, nonlinear relationships in data and improve their performance over time through experience

. In summary, a neural network is an AI model that simulates brain-like processing to analyze data, learn from it, and make intelligent decisions or predictions.