Lesson 37 - Module 12 Machine Learning Version 1 CSE IIT,...

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Module 12 Machine Learning Version 1 CSE IIT, Kharagpur
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Lesson 37 Learning and Neural Networks - I Version 1 CSE IIT, Kharagpur
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12.4 Neural Networks Artificial neural networks are among the most powerful learning models. They have the versatility to approximate a wide range of complex functions representing multi- dimensional input-output maps. Neural networks also have inherent adaptability, and can perform robustly even in noisy environments. An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information. The key element of this paradigm is the novel structure of the information processing system. It is composed of a large number of highly interconnected simple processing elements (neurons) working in unison to solve specific problems. ANNs, like people, learn by example. An ANN is configured for a specific application, such as pattern recognition or data classification, through a learning process. Learning in biological systems involves adjustments to the synaptic connections that exist between the neurons. This is true of ANNs as well. ANNs can process information at a great speed owing to their highly massive parallelism. Neural networks, with their remarkable ability to derive meaning from complicated or imprecise data, can be used to extract patterns and detect trends that are too complex to
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This note was uploaded on 09/20/2010 for the course MCA DEPART 501 taught by Professor Hemant during the Fall '10 term at Institute of Computer Technology College.

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Lesson 37 - Module 12 Machine Learning Version 1 CSE IIT,...

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