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Extends in Artificial Intelligence 4 | Issue 1 | Pages 8086ISSN: 26436000Review Article DOI: 10.36959/643/306The Holdup of the Century: Neural Networks are Coming from Cognitive Science and not Machine

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Neural networks are computational models inspired by the human brain's network of neurons, designed to recognize patterns and solve complex problems in machine learning.

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Filling out neural networks and machine involves providing detailed documentation of the neural network architecture, data used, training methods, and performance metrics, often following a specific regulatory or institutional guideline.

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The purpose of neural networks is to enable machines to learn from data, recognizing patterns, making decisions, and performing tasks that typically require human intelligence.

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Information that must be reported includes the architecture of the network, training dataset characteristics, performance evaluation results, and any ethical considerations related to its deployment.

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