Shallow and deep learning principles : scientific, philosophical, and logical perspectives / Zekai Sen
2023
QA76.87
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Details
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
3031295552 (electronic bk.)
3031295544
9783031295546
Published
Cham : Springer, [2023]
Language
English
Description
1 online resource
Item Number
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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Table of Contents
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.
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.