In this weekly Office Hours for Oracle Machine Learning on Autonomous Database, where introduced the latest Notebook templates for Machine Learning Clustering problems. This was a follow-along Session, since the OML Notebook templates are available to any Autonomous Database tenancy, and people were able to run it while we demonstrated it.
We also discussed the Oracle Data Miner setup and connectivity from SQL Developer Desktop, which is now compatible with Autonomous Database.
The Oracle Machine Learning product family supports data scientists, analysts, developers, and IT to achieve data science project goals faster while taking full advantage of the Oracle platform.
Oracle Machine Learning Notebooks offers an easy-to-use, interactive, multi-user, collaborative interface based on Apache Zeppelin notebook technology, and supports SQL, PL/SQL, Python and Markdown interpreters. It is available on all Autonomous Database versions and tiers, including Always-Free.
Oracle Machine Learning for Python includes AutoML, which provides automated machine learning features for algorithm selection, feature selection, and model tuning for in-database algorithms. In addition, Oracle Machine Learning AutoML UI provides a no-code user interface for the modeling process to enhance data scientist productivity while empowering non-experts with in-database machine learning. OML AutoML UI is exclusive to the Autonomous Database.
OML Services, which is also included with Autonomous Database provides a REST interface for model deployment and management. OML Services supports in-database models as well as ONNX-format models (for classification, regression and clustering) built using third-party engines. OML Services also supports cognitive text analytics in English, French, Spanish and Italian.