Join us on this weekly Office Hours for Oracle Machine Learning on Autonomous Database, where Sajith Vijayan, Sr Director, Data Science for Retail, and Su-Ming Wu, Sr. Principal Data Scientist, will present how OML algorithms are leveraged in the Retail Science platform, and more particularly in Oracle’s point-of-sale solution, Oracle Retail XBRi Loss Prevention.

They will illustrate how they can provide tools to avoid fraud by cashiers as well as fraud tied to customers’ accounts, where OML recommends a way to do fraud detection and a more general outlier detection. The solution flags outlier cashier behavior or outlier customer behavior, and can deliver the information to the retailer for further investigation.

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 is also included in Autonomous Database, where you can deploy and manage native in-database OML models as well as ONNX ML models (for classification and regression) built using third-party engines, and can also invoke cognitive text analytics.