närvivõrkudena

Närvivõrkudena refers to the Estonian term for artificial neural networks. These are computational models inspired by the structure and function of biological neural networks, which form animal brains. The fundamental unit of a neural network is the artificial neuron, also known as a node or unit. These neurons are interconnected, and each connection has a weight associated with it. These weights are adjusted during a learning process to enable the network to perform specific tasks.

Neural networks are typically organized in layers. The input layer receives the raw data, the output layer produces the final result, and one or more hidden layers process the information between the input and output. The processing within a neuron involves summing the weighted inputs and then applying an activation function to produce an output. This output is then passed to other neurons.

The learning process in neural networks, often referred to as training, involves presenting the network with a dataset and adjusting the weights to minimize errors in its predictions. Common learning algorithms include backpropagation. Närvivõrkudena are widely used in various fields, including pattern recognition, machine learning, natural language processing, and computer vision. Their ability to learn complex patterns from data makes them powerful tools for solving a wide range of problems.