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September 21, 2021

15:00 UTC   Start Times Around the World

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OML usage highlight: Live Demo of Oracle Stream Analytics with OML AutoML UI and OML Services
Join us on this weekly Office Hours for Oracle Machine Learning on Autonomous Database, where Hadi Javaherian, Senior AppDev and Integration Platform Specialist will explain all the benefits of the integration between Oracle Stream Analytics and Oracle Machine Learning Services. He will share how this is directly related to the concept of Data Mesh at a high level, and will also show how easy it is for a user to create models using OML AutoML UI and deploy them in seconds to OML Services, which then are made available immediately to Oracle Stream Analytics for real time scoring.

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.

Video highlights
00:40 Topics for Today
00:52 Upcoming Sessions
01:34 GGSA and AutoML UI - Data Mesh in Practice
02:31 Data Fabric, Stream Processing and Data Mesh
03:04 Data Capital
03:28 Attributes of a Trusted Data Mesh
05:15 Data Products
06:08 A Decentralized Mesh
07:23 Streaming Data Pipelines
08:03 GoldenGate Stream Analytics
08:58 Tangible, Trusted Data Products
10:15 AutoML UI Experiment - OML Simplified
10:55 GGSA and AutoML UI Integration
12:33 Data Mesh with Stream Analytics and AutoML UI
14:37 Live Demo - Oracle Stream Analytics
16:18 Live Demo - Oracle Machine Learning AutoML UI
17:09 Live Demo - OML Models
17:58 Live Demo - Oracle Stream Analytics
21:42 Q&A

Your Experts

    Hadi Javaherian

    Hadi Javaherian

    Hadi Javaherian is an Integration specialist with the AppDev and Integration Team at Oracle. He has been working as a software Engineer and an Architect for the past 20 years in industries such as Commercial, Aerospace and Defense and Telecommunication. Hadi specializes in the areas of AI and Machine Learning, Oracle GoldenGate and Big Data including Stream Analytics as well as the Oracle Middleware stack and Blockchain. He holds a Bachelor’s degree in Mechanical Engineering and a Master's degree in Artificial Intelligence and has done extensive postgraduate work in Thermodynamics and Energy.
    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.
    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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