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February 28, 2023

16:00 UTC   Start Times Around the World

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Description

Feature Highlight: Data and Model Monitoring in Autonomous Database
Machine Learning models are increasingly used to make business decisions in production environments. It is critical to ensure that these models make accurate predictions and are robust to shifts in the data.

Oracle Machine Learning Services extends OML functionality in Autonomous Database to support model deployment and model lifecycle management via REST APIs. In the coming weeks, data and model monitoring capabilities will be introduced. With these features, users can track the accuracy of their machine learning models in production and understand data trends by viewing performance degradation alerts. Join us to learn about these upcoming features and see demonstrations using cURL and Postman.
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This session: https://asktom.oracle.com/pls/apex/asktom.search?oh=20483

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Your Experts

  • #SELECTION#
    Miles Novotny

    Miles Novotny

    I am a Solution Engineer working out of the North America Specialist Hub who specializes in analytics solutions and has a strong interest in machine learning.
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    Sherry LaMonica

    Sherry LaMonica

    Sherry is a member of the Oracle Machine Learning Product Management team. She has 20 years of software experience focused on enabling the commercial use of the open-source data analysis software systems R and Python for data science and machine learning projects. She has worked with customers in fields as diverse as as pharmaceutical research, financial analysis, manufacturing and healthcare IT.
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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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