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April 20, 2021

15:00 UTC   Start Times Around the World

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Description

OML usage highlight: Oracle Stream Analytics with Real-time OML Services scoring
In this Office Hours for Oracle Machine Learning on Autonomous Database, Thomas Vengal, Director of Product Management for Oracle Stream Analytics (OSA/OEP) and Oracle GoldenGate provided the architecture and demo of using the Oracle Stream Analytics with direct calls for scoring OML models using the OML Services REST APIs in real-time.

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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    Marcos Arancibia

    Marcos Arancibia   

    Marcos Arancibia is a Senior Principal Product Manager in the Oracle Autonomous Database team. He is charted with developing a comprehensive platform for enabling all customers and use cases to be successful on Autonomous Database, and working with developers to bring their Applications and workloads as well. Within Product Management he works to develop product strategy, roadmap prioritization, product positioning and product evangelization, working closely with the engineering teams in defining the product roadmap for Autonomous Database. He previously was a PM for Oracle Machine Learning, and before joining Oracle in 2010 he spent 13 years at SAS Institute Inc., from Country Manager in LAD to Regional Data Mining lead in the US. He holds a bachelor's degree with additional courses in the master's degree, both in Statistics from UNICAMP in Brazil. He has Certifications from Stanford on AI and Machine Learning, and from the University of Washington on Computational Neuroscience.
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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, and working with internal and external customers in applying Oracle’s machine learning technologies for scalable and deployable data science projects. Mark is Oracle’s representative to the R Consortium and an Oracle adviser and founding member of the Analytics and Data Oracle User Community. He holds a bachelor's degree from Rutgers University and a master's degree from Brown University, both in Computer Science.
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    Thomas Vengal

    Thomas Vengal   

    Thomas Vengal is the Director of Product Management for Oracle GoldenGate and Stream Analytics products. He is an expert technology leader for data platforms, big data, data integration, machine learning, and application management. Prior to Oracle, Thomas was leading product management for Informatica Data Platform and product development of Hewlett-Packard Business Service Management software Products. He holds an MBA from Perth Graduate School of Business in Australia and a Master of Technology in Data Science and Engineering from BITS Pilani in India. He holds several industry certifications and has published international papers and disclosures.
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