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Oracle Machine Learning Office Hours

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November 09

16:00 UTC   Start Times Around the World

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Description

OML Usage Highlight: Leveraging OML algorithms in Retail Science platform - Fraud Detection
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.

Your Experts

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    Su-Ming Wu

    Su-Ming Wu

    Su-Ming has been a data scientist at Oracle for 10 years, and has worked in various areas of retail science, including assortment planning, price optimization, and demand forecasting. He has a Ph.D. in mathematics, and a master's degree in computer science.
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    Sajith Vijayan

    Sajith Vijayan

    Sajith Vijayan is the Sr Director, Data Science at Oracle for 10+ years. He leads the development and productization of Retail AI/ML solutions using OML. He has a Master’s Degree in computer science and a MBA in Enterpernship
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    Mark Hornick

    Mark Hornick   

    Mark Hornick is the Senior Director of Product Management for the Oracle Machine Learning (OML) family of products. He leads the OML PM team and works closely with Product Development on product strategy, positioning, and evangelization, Mark has over 20 years of experience with integrating and leveraging machine learning with Oracle technologies, working with internal and external customers in the application of Oracle’s machine learning technologies for scalable and deployable data science projects. Mark is Oracle’s representative on the R Consortium’s Board of Directors, an Oracle Adviser and founding member of the Business Intelligence Warehousing and Analytics (BIWA) User Community, and Content Selection Committee Chair for the Analytics and Data Summits.
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