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|a ABES
|b fre
|e AFNOR
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|a eng
|2 639-2
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|a Q325.5
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|0 (IdRef)192458744
|1 http://www.idref.fr/192458744/id
|a Withanawasam
|d (Jayani).
|4 aut.
|e Auteur
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| 245 |
1 |
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|a Apache Mahout essentials :
|b implement top-notch machine learning algorithms for classification, clustering, and recommendations with Apache Mahout
|c Jayani Withanawasam.
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| 246 |
1 |
3 |
|a Implement top-notch machine learning algorithms for classification, clustering, and recommendations with Apache Mahout
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| 256 |
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|a Données textuelles (1 fichier PDF).
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| 264 |
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1 |
|a Birmingham :
|b Packt Publishing,
|c 2015.
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| 336 |
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|b txt
|2 rdacontent
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|b c
|2 rdamedia
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|b b
|2 isbdmedia
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|b ceb
|2 RDAfrCarrier
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1 |
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|a Community experience distilled
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|a Titre provenant de l'écran-titre.
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|a Numérisation de l'édition de Birmingham : Packt publishing, cop. 2015.
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|a L'impression du document génère 165 pages.
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|a Description d'après la consultation, 2016-04-12.
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|a L'accès à cette ressource est réservé aux usagers des établissements qui en ont fait l'acquisition
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|a Apache Mahout is a scalable machine learning library with algorithms for clustering, classification, and recommendations. It empowers users to analyze patterns in large, diverse, and complex datasets faster and more scalably. This book is an all-inclusive guide to analyzing large and complex datasets using Apache Mahout. It explains complicated but very effective machine learning algorithms simply, in relation to real-world practical examples. Starting from the fundamental concepts of machine learning and Apache Mahout, it guides you through Apache Mahout's implementations of machine learning techniques including classification, clustering, and recommendations. Real-world applications, a diverse range of popular algorithms and their implementations, code examples, evaluation strategies, and best practices are given for each technique. You will learn data visualization techniques for Apache Mahout to bring your data to life. --
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| 538 |
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|a Configuration requise : navigateur internet.
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|a Mahout (Electronic resource).
|2 lc
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| 650 |
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|a Machine learning.
|2 lc
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| 650 |
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|a Artificial intelligence.
|2 lc
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| 650 |
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|0 (IdRef)027940373
|1 http://www.idref.fr/027940373/id
|a Apprentissage automatique.
|2 ram
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| 650 |
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7 |
|0 (IdRef)167193686
|1 http://www.idref.fr/167193686/id
|a Données massives.
|2 ram
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| 650 |
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7 |
|0 (IdRef)027282171
|1 http://www.idref.fr/027282171/id
|a Algorithmes.
|2 ram
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| 760 |
0 |
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|t Open source* : community experience distilled
|d Birmingham : Packt publishing, 2013
|w (ABES)172618363
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| 830 |
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|a Open source*.
|f 2013
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| 856 |
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|q HTML
|u https://srvext.uco.fr/login?url=https://univ.scholarvox.com/book/88853031
|w Données éditeur
|z Accès à l'E-book
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|2 unimarc
|a 181
|a i#
|b xxxe##
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|a E-Book
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|a BNUM
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|a 192458701
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