Neural Network: Difference between revisions
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Neural networks are a type of [[artificial intelligence]] inspired by the way the human brain works. They consist of layers of interconnected nodes, or "neurons," that process data by passing signals from input to output layers. The connections between these neurons can be adjusted or "learned" based on the data they process, allowing the network to identify patterns and make decisions. Neural networks are used in a wide range of applications, from recognizing speech and images to making predictions and understanding [[Natural Language Processing|natural language]]. They form the basis of [[Deep Learning|deep learning]], a subset of [[Machine Learning|machine learning]] techniques that involve networks with many layers. | |||
Latest revision as of 15:06, 2 February 2024
Neural networks are a type of artificial intelligence inspired by the way the human brain works. They consist of layers of interconnected nodes, or "neurons," that process data by passing signals from input to output layers. The connections between these neurons can be adjusted or "learned" based on the data they process, allowing the network to identify patterns and make decisions. Neural networks are used in a wide range of applications, from recognizing speech and images to making predictions and understanding natural language. They form the basis of deep learning, a subset of machine learning techniques that involve networks with many layers.