@article{1437390,
      recid = {1437390},
      author = {Helshyaho, Heli, and Yu, Jean, and Yu, Kai,},
      title = {Machine learning for Oracle database professionals :  deploying model-driven applications and automation  pipelines /},
      pages = {1 online resource :},
      note = {Includes index.},
      abstract = {Database developers and administrators will use this book  to learn how to deploy machine learning models in Oracle  Database and in Oracles Autonomous 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 advanced topics  such as delivery and automation pipelines. Throughout the  book you will find practical details and hand-on examples  showing you how to implement machine learning and automate  deployment of machine learning. Discussion around the  examples helps you gain a conceptual understanding of  machine learning. Important concepts discussed include the  methods involved, the algorithms to choose from, and  mechanisms for process and deployment. Seasoned database  professionals looking to make the leap into machine  learning as a growth path will find much to like in this  book as it helps you step up and use your current knowledge  of Oracle Database to transition into providing machine  learning solutions. You will: Use the Oracle Machine  Learning (OML) Notebooks for data visualization and machine  learning model building and evaluation Understand Oracle  offerings for machine learning Develop machine learning  with Oracle database using the built-in machine learning  packages Develop and deploy machine learning models using  OML4SQL and OML4R Leverage the Oracle Autonomous Database  and its collaborative environment for Oracle Machine  Learning Develop and deploy machine learning projects in  Oracle Autonomous Database Build an automated pipeline that  can detect and handle changes in data/model performance.},
      url = {http://library.usi.edu/record/1437390},
      doi = {https://doi.org/10.1007/978-1-4842-7032-5},
}