Psychology Dictionary of Arguments

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 Neural Networks - Psychology Dictionary of Arguments
 
Neural networks: Neural networks are computational models inspired by the human brain, designed to recognize patterns and solve complex problems. They consist of layers of interconnected nodes (analogous to neurons) that process input data and learn to perform tasks by adjusting the strength of connections based on feedback. Used extensively in machine learning, they enable applications like image recognition, language processing, and predictive analysis. See also Artificial Neural networks, Connectionism, Computer models, Computation, Artificial Intelligence, Machine learning.
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Annotation: The above characterizations of concepts are neither definitions nor exhausting presentations of problems related to them. Instead, they are intended to give a short introduction to the contributions below. – Lexicon of Arguments.
 
Author Item    More concepts for author
Anderson, Chris Neural Networks   Anderson, Chris
Deacon, Terrence W. Neural Networks   Deacon, Terrence W.
Dyson, George Neural Networks   Dyson, George
Mareschal, Denis Neural Networks   Mareschal, Denis
McCulloch, Warren Neural Networks   McCulloch, John Ramsay
Minsky, Marvin Neural Networks   Minsky, Marvin
Norvig, Peter Neural Networks   Norvig, Peter
Pitts, Walter Neural Networks   Pitts, Walter
Rumelhart, David E. Neural Networks   Rumelhart, David E.
Wolfram, Stephen Neural Networks   Wolfram, Stephen

Authors A   B   C   D   E   F   G   H   I   J   K   L   M   N   O   P   Q   R   S   T   U   V   W   Z  


Concepts A   B   C   D   E   F   G   H   I   J   K   L   M   N   O   P   Q   R   S   T   U   V   W   Y   Z  


Ed. Martin Schulz, access date 2024-03-28