Abstract
An information processing paradigm called an Artificial Neural Network (ANN) is based on how biological nervous systems, like the brain, process information. The information processing system's novel structure is the paradigm's most important feature. It is made up of many highly interconnected processing elements (neurons) that work together to solve particular problems. Similar to humans, ANNs learn from examples. Through a learning process, an ANN is set up for a specific use, like pattern recognition or data classification. Changing the neuronal synaptic connections is necessary for learning in biological systems. This is also true for ANNs. This paper provides an overview of the Artificial Neural Network, its operation, and its training. Additionally, it describes the advantages and applications of ANN.
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