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Neural network - Wikipedia
A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or mathematical models. While individual neurons are simple, many of them together in a network can perform complex tasks. There are two main types of neural networks.

What is a Neural Network? - GeeksforGeeks
Neural networks are machine learning models that mimic the complex functions of the human brain. These models consist of interconnected nodes or neurons that process data, learn patterns, and enable tasks such as pattern recognition and decision-making.

What is a Neural Network? - IBM
What is a neural network? A neural network is a machine learning program, or model, that makes decisions in a manner similar to the human brain, by using processes that mimic the way biological neurons work together to identify phenomena, weigh options and arrive at conclusions.

What is a neural network? | Types of neural networks
A neural network, or artificial neural network, is a type of computing architecture that is based on a model of how a human brain functions — hence the name "neural." Neural networks are made up of a collection of processing units called "nodes."

Explained: Neural networks - MIT News
Neural nets are a means of doing machine learning, in which a computer learns to perform some task by analyzing training examples. Usually, the examples have been hand-labeled in advance.

What is a Neural Network? - Artificial Neural Network Explained - AWS
A neural network is a method in artificial intelligence (AI) that teaches computers to process data in a way that is inspired by the human brain. It is a type of machine learning (ML) process, called deep learning, that uses interconnected nodes or neurons in a layered structure that resembles the human brain.

What Are Neural Networks? The Backbone of Modern AI Explained
In this article, we explore what neural networks are, how they work, and their key applications in modern AI. Learn how these brain-inspired models power technologies like image recognition, speech processing, and more.

A Beginner's Guide to Neural Networks and Deep Learning
Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling or clustering raw input.

How neural networks work - A simple introduction - Explain that Stuff
With the help of neural networks —computer programs assembled from hundreds, thousands, or millions of artificial brain cells that learn and behave in a remarkably similar way to human brains. What exactly are neural networks? How do they work? Let's take a closer look!

What Is a Neural Network? A Deep Dive into the Brain Behind AI
At its core, a neural network is a mathematical model that tries to mimic the way biological neurons in the brain process and transmit information. It’s this brain-like architecture that allows machines to learn, recognize patterns, and even make decisions.

 

 

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Stock market trend prediction using deep neural network via chart analysis: a practical method or a myth?  Nature

An explanation of neural networks  TechTarget

Integrative fault diagnostic analytics in transformer windings: Leveraging logistic regression, discrete wavelet transform, and neural networks  ScienceDirect.com

Data Science vs Machine Learning vs Data Analytics [2025]  Simplilearn.com

Artificial Neural Networks Global Strategic Business Report 2024: Market to Reach $1.5 Billion by 2030 - Unlocking New Possibilities in Drug Discovery, Renewable Energy, and Beyond  GlobeNewswire

Enhancing Activation Energy Predictions under Data Constraints Using Graph Neural Networks  ACS Publications

Neural Networks vs AI – Decoding the Differences  sify.com

Deep learning in microbiome analysis: a comprehensive review of neural network models  Frontiers

Neural-network analysis posits how brains build skills  The Transmitter

A Unified Neural Network Framework for Extended Redundancy Analysis  Cambridge University Press & Assessment

Framework tracks 'learning curve' of AI to decode complex genomic data  Phys.org

Neural Network Uses Weather Data to Boost Energy Efficiency in the Oil and Gas Industry  Society of Petroleum Engineers (SPE)

Comparative Analysis of Recurrent Neural Networks with Conjoint Fingerprints for Skin Corrosion Prediction  ACS Publications

An efficient artificial neural network-based optimization techniques for the early prediction of coronary heart disease: comprehensive analysis  Nature

Optimizing quantum convolutional neural network architectures for arbitrary data dimension  Frontiers

 

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