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211025 ||| eng |
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4 |
|a Q325.5
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| 100 |
1 |
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|a Deza, Alfredo
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| 245 |
0 |
0 |
|a MLOps maturity model
|c Alfredo Deza
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| 250 |
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|a [First edition]
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| 260 |
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|a [Place of publication not identified]
|b Pragmatic AI Solutions
|c 2021
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| 300 |
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|a 1 video file (19 min.)
|b sound, color
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| 653 |
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|a Machine learning / http://id.loc.gov/authorities/subjects/sh85079324
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| 653 |
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|a Apprentissage automatique
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| 653 |
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|a Machine learning / fast / (OCoLC)fst01004795
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| 700 |
1 |
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|a Gift, Noah
|e presenter
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 856 |
4 |
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|u https://learning.oreilly.com/videos/~/50121VIDEOPAIML/?ar
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 006.3/1
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| 520 |
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|a Get some clarity on MLOps, what it is, and what does it mean to be "doing MLOps" by using a maturity model. A maturity model allows you to accurately determine where in the process of applying MLOps best-practices your team is. In this video, I'll explain some of the challenges with MLOps and why it might be difficult to understand some of its processes. This knowledge gap is what the Practical MLOps book tries to address, by clarifying and simplifying what needs to happen. Topics include: * Explain the Machine Learning Operations Maturity Model * Use techniques to strategize the next steps in a model's lifecycle * Accurately determine what might the next step towards model automation will be Useful links: * Azure Maturity Model
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