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01564nam a22003973i 4500 |
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MiAaPQ |
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20231204023228.0 |
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|a 9789811951701
|q (electronic bk.)
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|z 9789811951695
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|a (MiAaPQ)EBC7165982
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|a (Au-PeEL)EBL7165982
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|a (OCoLC)1378936185
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|a Q334-342
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|a Bartz, Eva.
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|a Hyperparameter Tuning for Machine and Deep Learning with R :
|b A Practical Guide.
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| 250 |
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|a 1st ed.
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| 264 |
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|a Singapore :
|b Springer,
|c 2023.
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| 264 |
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|c Ã2023.
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| 300 |
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|a 1 online resource (327 pages)
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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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| 588 |
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|a Description based on publisher supplied metadata and other sources.
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| 590 |
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|a Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2023. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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| 655 |
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|a Electronic books.
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| 700 |
1 |
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|a Bartz-Beielstein, Thomas.
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| 700 |
1 |
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|a Zaefferer, Martin.
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| 700 |
1 |
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|a Mersmann, Olaf.
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| 776 |
0 |
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|i Print version:
|a Bartz, Eva
|t Hyperparameter Tuning for Machine and Deep Learning with R
|d Singapore : Springer,c2023
|z 9789811951695
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| 797 |
2 |
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|a ProQuest (Firm)
|
| 856 |
4 |
0 |
|u https://ebookcentral.proquest.com/lib/matrademy/detail.action?docID=7165982
|z Click to View
|
