On this Office Hours for Oracle Machine Learning on Autonomous Database, we introduced the latest Notebook templates for Machine Learning Feature Extraction for Text problems, using Explicit Semantic Analysis (ESA). This was follow-along Session, since the OML Notebook templates are available to any Autonomous Database tenancy, and you were able to run it while we demonstrated it.

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.

The Oracle Machine Learning Notebooks offers an easy-to-use, interactive, multi-user, collaborative interface based on Apache Zeppelin notebook technology, and support SQL, PL/SQL, Python and Markdown interpreters. It is available on all Autonomous Database versions and Tiers, including the always-free editions.

OML includes AutoML, which provides automated machine learning algorithm features for algorithm selection, feature selection and model tuning, in addition to a specialized AutoML UI 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.