A neural network is a machine learning model inspired by the way interconnected neurons process information. It consists of layers of connected computational units that transform input data step by step, allowing the model to learn patterns and relationships from examples. During training, the network adjusts its internal parameters to improve its ability to produce useful outputs.
For example, a neural network trained on images can learn visual patterns that help it distinguish between different objects. Earlier layers may recognize basic features such as edges and shapes, while deeper layers combine those features into more complex representations. Neural networks are widely used in computer vision, speech recognition, natural language processing, recommendation systems, robotics, forecasting, and generative AI.
