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Artificial neural networks have been recognized as a powerful tool to learn and reproduce systems in various fields of applications. Structural learning consists of learning the topology of the network, that is, the number of layers, the number of neurons in each layer, and what neurons are connected.
This title presents a unique, non-standard approach to solving problems in linear algebra. Enrique Castillo, highly-regarded author of applied mathematics texts, discusses topics in four major parts, covering the basic theory of linear systems, solving linear inequalities, linear programming, and applications.
Artificial neural networks have been recognized as a powerful tool to learn and reproduce systems in various fields of applications. Structural learning consists of learning the topology of the network, that is, the number of layers, the number of neurons in each layer, and what neurons are connected.
Tilmeld dig nyhedsbrevet og få gode tilbud og inspiration til din næste læsning.
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