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Shallow and Deep Learning Principles

Scientific, Philosophical, and Logical Perspectives

Zekâi Şen

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ca. 171,19 €
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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Elektronik, Elektrotechnik, Nachrichtentechnik

Beschreibung

This book discusses Artificial Neural Networks (ANN) and their ability to predict outcomes using deep and shallow learning principles. The author first describes ANN implementation, consisting of at least three layers that must be established together with cells, one of which is input, the other is output, and the third is a hidden (intermediate) layer. For this, the author states, it is necessary to develop an architecture that will not model mathematical rules but only the action and response variables that control the event and the reactions that may occur within it. The book explains the reasons and necessity of each ANN model, considering the similarity to the previous methods and the philosophical - logical rules.

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Schlagwörter

Machıne Learnıng, Artıfıcıal Intellıgence, Uncertainty and Modeling Principles, Mathematical Modeling Principles, Artificial Neural Networks, Philosophical and Logical Principles in Science, Genetic Algorithm