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Titlebook: Machine Learning for Oracle Database Professionals; Deploying Model-Driv Heli Helskyaho,Jean Yu,Kai Yu Book 2021 Heli Helskyaho, Jean Yu, K

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41#
發(fā)表于 2025-3-28 15:37:55 | 只看該作者
Building Machine Learning Models with OML Notebooks,etched from Oracle Autonomous Database. Through these key features, Oracle Machine Learning (OML) in Oracle Autonomous Database provides an excellent platform for various machine learning development projects. This chapter is dedicated to exploring how to leverage this platform for machine learning projects.
42#
發(fā)表于 2025-3-28 21:56:21 | 只看該作者
Oracle Analytics Cloud, in the machine learning process, and OAC is a very good tool for that, especially because of its augmented capabilities. Augmented analytics is powered by machine learning. OAC supports integration very well by allowing users to add data from many different data sources, including Oracle SaaS applications.
43#
發(fā)表于 2025-3-29 00:08:29 | 只看該作者
ML Deployment Pipeline Using Oracle Machine Learning, massive data sets. The current trend is to operate the ML platform as a centralized service for the entire enterprise, enabling efficient, uniform, reliable, and reproducible pipelines across many organizations.
44#
發(fā)表于 2025-3-29 03:49:01 | 只看該作者
Book 2021s Database cloud offering. The book covers the technologies that make up the Oracle Machine Learning (OML) platform, including OML4SQL, OML Notebooks, OML4R, and OML4Py. The book focuses?on Oracle Machine Learning as part of the Oracle Autonomous Database collaborative environment. Also covered are
45#
發(fā)表于 2025-3-29 07:52:39 | 只看該作者
https://doi.org/10.1007/978-1-4842-7032-5Machine Learning; Oracle Database; PL/SQL; Python; R; Jupyter Notebooks; Oracle Autonomous Database; Oracle
46#
發(fā)表于 2025-3-29 12:20:48 | 只看該作者
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