Neural Networks

Definition of Neural Networks as it relates to Science, Computer Science, Algorithms

Neural Networks are algorithms designed to recognize patterns and learn from data, inspired by the structure and function of biological brains. They consist of interconnected layers of nodes, or artificial neurons, that process information through a series of weighted connections. The networks "learn" by adjusting these weights based on the data they're trained on, enabling them to make predictions, classify data, or generate new content. In this context, Neural Networks are a powerful tool within the broader field of Algorithms in Computer Science, which is itself part of the wider discipline of Science. They can be used for tasks such as image and speech recognition, natural language processing, and even game playing, making them an essential component of modern artificial intelligence systems.

Note
  • [DeepNeuralNetworks.net]
  • [bionn.matinf.uj.edu.pl] Bio-inspired artificial neural networks
  • [snufa.net] SNUFA | Spiking Neural networks as Universal Function Approximators
  • [holger-arndt.com] Holger Arndt | Big Data Analytics, Machine Learning, Neural Networks
  • [rnns.net] RNNS — Official site of Russian Neural Network Society
  • [nnql.org] NNQL Neural Network Query Language
  • [pfr.com] Parallax Financial Research – Neural Network Solutions for Professional Money Managers
Related Categories ⇒