Närvivõrgustik

Närvivõrgustik, also known as neural networks, is a subset of machine learning and artificial intelligence that is inspired by the structure and function of biological neural networks. It consists of interconnected nodes, or neurons, that process information and transmit signals to each other. These networks are designed to recognize patterns and make decisions based on input data.

The basic unit of a neural network is the artificial neuron, which mimics the behavior of biological neurons. Each neuron receives input signals, processes them using a mathematical function, and produces an output signal. The strength of the connections between neurons, known as weights, is adjusted during the training process to improve the network's performance.

Neural networks can be categorized into different types based on their structure and function. Feedforward neural networks, for example, have a unidirectional flow of information from input to output layers. Recurrent neural networks, on the other hand, have connections that form directed cycles, allowing them to process sequential data. Convolutional neural networks are specifically designed for image and video processing, using convolutional layers to extract features from input data.

Neural networks have a wide range of applications, including image and speech recognition, natural language processing, and game playing. They have also been used in various fields such as healthcare, finance, and transportation to analyze complex data and make predictions. However, neural networks also face challenges such as the need for large amounts of data and computational resources, as well as issues related to interpretability and generalization.