Shallow and deep learning principles : scientific, philosophical, and logical perspectives / Zekai Sen
Sen, Zekai, author.
2023
QA76.87
Available Online

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Title Shallow and deep learning principles : scientific, philosophical, and logical perspectives / Zekai Sen
Author Sen, Zekai, author.
ISBN 9783031295553 (electronic bk.)
3031295552 (electronic bk.)
3031295544
9783031295546
DOI https://doi.org/10.1007/978-3-031-29555-3
Published Cham : Springer, [2023]
Language English
Description 1 online resource
Other Standard Identifiers 10.1007/978-3-031-29555-3 doi
Call Number QA76.87
Dewey Decimal Classification 006.32
Summary 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.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Available in Other Form Print version: 9783031295546
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Introduction
Philosophical and Logical Principles in Science
Uncertainty and Modeling Principles
Mathematical Modeling Principles
Genetic Algorithm
Artificial Neural Networks
Artfcal Intellgence
Machne Learnng
Deep Learning
Conclusion.

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