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00000cam a22000007i 4500 |
| 001 |
on1381107322 |
| 003 |
OCoLC |
| 005 |
20241006213017.0 |
| 006 |
m o d |
| 007 |
cr cnu---unuuu |
| 008 |
230605s2023 sz o 001 0 eng d |
| 040 |
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|a YDX
|b eng
|e rda
|c YDX
|d EBLCP
|d GW5XE
|d UKAHL
|d OCLCF
|d OH1
|d YDX
|d OCLCO
|d SFB
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| 019 |
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|a 1381712232
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| 020 |
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|a 9783031295553
|q electronic book
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| 020 |
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|a 3031295552
|q electronic book
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| 020 |
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|z 3031295544
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| 020 |
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|z 9783031295546
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| 024 |
7 |
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|a 10.1007/978-3-031-29555-3
|2 doi
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| 035 |
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|a (OCoLC)1381107322
|z (OCoLC)1381712232
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| 050 |
|
4 |
|a QA76.87
|b .S46 2023
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| 049 |
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|a HCDD
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| 100 |
1 |
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|a Sen, Zekai,
|e author.
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| 245 |
1 |
0 |
|a Shallow and deep learning principles :
|b scientific, philosophical, and logical perspectives /
|c Zekai Sen
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| 264 |
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1 |
|a Cham :
|b Springer,
|c [2023]
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| 300 |
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|a 1 online resource
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| 336 |
|
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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| 338 |
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|a online resource
|b cr
|2 rdacarrier
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| 504 |
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|a Includes bibliographical references and index.
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| 505 |
0 |
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|a 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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| 520 |
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|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.
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| 650 |
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0 |
|a Neural networks (Computer science)
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| 650 |
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0 |
|a Machine learning.
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| 650 |
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7 |
|a Machine learning
|2 fast
|
| 650 |
|
7 |
|a Neural networks (Computer science)
|2 fast
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| 776 |
0 |
8 |
|c Original
|z 3031295544
|z 9783031295546
|w (OCoLC)1371402151
|
| 856 |
4 |
0 |
|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-031-29555-3
|y Click for online access
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| 903 |
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|a SPRING-ALL2023
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| 994 |
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|a 92
|b HCD
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