Neuronhálózatban

Neuronhálózatban is a Hungarian term that translates to "in a neural network." It refers to the context or operation within a computational system designed to mimic the structure and function of biological neural networks. These artificial neural networks are composed of interconnected nodes, or artificial neurons, organized in layers. Each connection between neurons has an associated weight, which is adjusted during the learning process. The "in a neural network" context implies processing information, performing computations, or undergoing training within this framework.

When data is processed neuronhálózatban, it typically passes through the input layer, then through one or more hidden layers, and finally reaches the output layer. Each artificial neuron receives input signals, applies an activation function to these inputs, and then transmits an output signal to other neurons. The weights of the connections determine the strength and influence of these signals. Learning in a neural network involves modifying these weights based on a given dataset and a learning algorithm, such as backpropagation, to minimize errors and improve performance on a specific task. This iterative process allows the network to learn patterns, make predictions, or classify data. The term is used broadly in discussions related to artificial intelligence, machine learning, and deep learning applications.