Artificial neural networks (ANNS) are computational models that are inspired by the structure and function of biological neural networks. ANNS consist of interconnected nodes that process and transmit information. There are various types of ANNs, including feedforward neural networks, recurrent neural networks, convolutional neural networks, and deep neural networks. Each type of ANN has a unique architecture and learning algorithm that enables it to perform specific tasks.

Principles of Information Systems (MindTap Course List)
13th Edition
ISBN:9781305971776
Author:Ralph Stair, George Reynolds
Publisher:Ralph Stair, George Reynolds
Chapter10: Knowledge Management And Specialized Information Systems
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Artificial neural networks (ANNS) are computational models that are inspired by the structure
and function of biological neural networks. ANNs consist of interconnected nodes that process
and transmit information. There are various types of ANNs, including feedforward neural
networks, recurrent neural networks, convolutional neural networks, and deep neural networks.
Each type of ANN has a unique architecture and learning algorithm that enables it to perform
specific tasks.
Transcribed Image Text:Artificial neural networks (ANNS) are computational models that are inspired by the structure and function of biological neural networks. ANNs consist of interconnected nodes that process and transmit information. There are various types of ANNs, including feedforward neural networks, recurrent neural networks, convolutional neural networks, and deep neural networks. Each type of ANN has a unique architecture and learning algorithm that enables it to perform specific tasks.
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