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200203s2019 xx 041 o vleng d |
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|a UMI
|b eng
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|d TOH
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|d OCLCQ
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|a (OCoLC)1138875689
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|a CL0501000090
|b Safari Books Online
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|a Q325.5
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|a UAMI
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|a Oppenheimer, Diego,
|e onscreen presenter.
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1 |
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|a Automating DevOps for machine learning /
|c Diego Oppenheimer.
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|a [Place of publication not identified] :
|b O'Reilly Media,
|c 2019.
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300 |
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|a 1 online resource (1 streaming video file (40 min., 10 sec.))
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|a two-dimensional moving image
|b tdi
|2 rdacontent
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|a computer
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|a video
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|a online resource
|b cr
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|a Title from resource description page (Safari, viewed January 31, 2020).
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|a Presenter, Diego Oppenheimer.
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|a "Learning common deployment architectures for machine learning in the real world and understanding how to build your model for a production environment can help you avoid pitfalls when scaling up. Diego Oppenheimer (Algorithmia) discusses common problems and solutions and shares best practices from leading organizations that have solved the deployment headache. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco."--Resource description page
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|a O'Reilly
|b O'Reilly Online Learning: Academic/Public Library Edition
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650 |
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0 |
|a Machine learning.
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650 |
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|a Software architecture.
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650 |
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|a Computer software
|x Development.
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650 |
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|a Apprentissage automatique.
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650 |
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|a Architecture logicielle.
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650 |
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|a Computer software
|x Development.
|2 fast
|0 (OCoLC)fst00872537
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650 |
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|a Machine learning.
|2 fast
|0 (OCoLC)fst01004795
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650 |
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7 |
|a Software architecture.
|2 fast
|0 (OCoLC)fst01200416
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655 |
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|a Electronic videos.
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|a O'Reilly Strata Data Conference
|d (2019 :
|c San Francisco, Calif.)
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856 |
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0 |
|u https://learning.oreilly.com/videos/~/0636920339908/?ar
|z Texto completo (Requiere registro previo con correo institucional)
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994 |
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|a 92
|b IZTAP
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