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Shallow and Deep Learning Principles

Shallow and Deep Learning Principles

Zekâi Şen

45,99 €
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Editorial:
Springer Nature B.V.
Año de edición:
2023
Materia
Ciencias de la computación
ISBN:
9783031295560
45,99 €
IVA incluido
Disponible

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Sobre IBD

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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