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August 16, 2022

15:00 UTC   Start Times Around the World

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Description

Using R to cluster data at scale in Autonomous Database
Some of the recent images of galaxies from the James Webb telescope highlight natural clustering in the universe. It's relatively easy to see clusters in two- or even three-dimensional images, but when confronted with significantly more dimensions, having advanced clustering algorithms can mean the difference between a "pile of data" and a meaningful understanding of, for example, customer segments. In this session, we'll touch on the different in-database clustering algorithms supported by Oracle Database and demonstrate these using the soon-to-be-released R interface of Oracle Machine Learning for R on Oracle Autonomous Database. This will be a fun and entertaining session that will cater to all levels of experience in OML.
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This session: https://asktom.oracle.com/pls/apex/asktom.search?oh=18842

Your Experts

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    Nicholas Cusato

    Nicholas Cusato

    Nicholas is a Solution Engineer working from the North America Specialist Hub, specializing in Data Management. He has a background in parallel programming and strong interest in supercomputing.
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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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