Artificial Neural Networks (ANNs) are computational models inspired by the biological neural networks of the human brain. They consist of interconnected nodes, or neurons, organized in layers, which process and analyze data. ANNs are a fundamental component of deep learning, enabling machines to recognize patterns, make decisions, and learn from experience. The architecture typically includes an input layer, one or more hidden layers, and an output layer, where each neuron applies an activation function to transform input data into meaningful outputs. ANNs are widely used in various applications, including image recognition, natural language processing, and predictive analytics.