Shallow and Deep Learning Principles Scientific, Philosophical, and Logical Perspectives /
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...
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| Natura: | Elettronico eBook |
| Lingua: | inglese |
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Cham :
Springer International Publishing : Imprint: Springer,
2023.
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| Edizione: | 1st ed. 2023. |
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| Accesso online: | https://doi.org/10.1007/978-3-031-29555-3 |
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| 245 | 1 | 0 | |a Shallow and Deep Learning Principles |h [electronic resource] : |b Scientific, Philosophical, and Logical Perspectives / |c by Zekâi Şen. |
| 250 | |a 1st ed. 2023. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2023. | |
| 300 | |a 1 online resource (XX, 661 p. 322 illus.). |b 71 illus. in color. | ||
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| 505 | 0 | |a Introduction -- Philosophical and Logical Principles in Science -- Uncertainty and Modeling Principles -- Mathematical Modeling Principles -- Genetic Algorithm -- Artificial Neural Networks -- Artıfıcıal Intellıgence -- Machıne Learnıng -- Deep Learning -- Conclusion. | |
| 520 | |a 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. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Telecommunication. | |
| 650 | 0 | |a Computer science |x Mathematics. | |
| 650 | 0 | |a Mathematical statistics. | |
| 650 | 0 | |a Technological innovations. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 1 | 4 | |a Communications Engineering, Networks. |
| 650 | 2 | 4 | |a Probability and Statistics in Computer Science. |
| 650 | 2 | 4 | |a Innovation and Technology Management. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
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| 776 | 0 | 8 | |i Printed edition: |z 9783031295546 |
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