---
title: "Neural Network"
description: "An artificial Neural Network is a computational model inspired by the way biological neural networks in the human brain process information. It consists of interconnected groups of artificial neurons, organized in layers, that work together to recognize patterns and solve complex problems. Each neuron receives input, processes it, and passes on the output to the next layer. Neural networks are a fundamental component of Deep Learning, a subset of Machine Learning, and are used extensively in tasks such as image and speech recognition, Natural Language Processing (NLP), and generative modeling. They are characterized by their ability to learn from data through a process called training, where the network adjusts its weights based on the error of its predictions to improve accuracy over time."
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---

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An artificial Neural Network is a computational model inspired by the way biological neural networks in the human brain process information. It consists of interconnected groups of artificial neurons, organized in layers, that work together to recognize patterns and solve complex problems. Each neuron receives input, processes it, and passes on the output to the next layer. Neural networks are a fundamental component of [Deep Learning](https://promptmetheus.com/resources/llm-knowledge-base/deep-learning), a subset of [Machine Learning](https://promptmetheus.com/resources/llm-knowledge-base/machine-learning-ml), and are used extensively in tasks such as image and speech recognition, [Natural Language Processing (NLP)](https://promptmetheus.com/resources/llm-knowledge-base/natural-language-processing-nlp), and generative modeling. They are characterized by their ability to learn from data through a process called training, where the network adjusts its weights based on the error of its predictions to improve accuracy over time.

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