Neural Networks

Neural networks, also known as artificial neural networks (ANNs), are a subset of machine learning and the foundation of deep learning algorithms. They consist of layers of interconnected nodes: an input layer, one or more hidden layers, and an output layer. Each node, or artificial neuron, has an associated weight and threshold. If the output of a node exceeds a specific threshold, it is activated and passes data to the next layer. Through a process called backpropagation, these networks adjust their weights based on the error of their output, allowing them to learn from data and improve accuracy over time. They are used for complex tasks such as image recognition, natural language processing, and predictive modeling.