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A **neural network** is a computational system designed to mimic the human brain’s structure and function. It consists of interconnected **nodes**, or **neurons**, arranged in **layers**: an input layer, one or more hidden layers, and an output layer. Each connection between nodes has a specific **weight**, which determines the strength of the signal passed from one neuron to another. During the **learning process**, a neural network adjusts these weights by analyzing vast amounts of **data** to identify patterns and make predictions. This process, often called **training**, allows the network to gradually improve its performance on tasks like image recognition or language translation. The ultimate goal of a neural network is to learn complex relationships within data without explicit programming for every rule.
