Neural Network Architecture
Neural Network Architecture refers to the structure and layout of interconnected nodes, or neurons, within a neural network. It encompasses the arrangement of layers, such as input, hidden, and output layers, as well as the connections and weights between neurons. Different architectures, such as feedforward, recurrent, and convolutional networks, are designed to perform specific tasks and optimize the learning process. The architecture plays a crucial role in determining the network's ability to learn and generalize from data, as well as its overall performance and efficiency.