There were many great talks again at Oracle Open World & Code One 2018! See the OOW'18 and Code One'18 Sessions Catalogs to see everything there.
For easy access and downloads, I'm posting my Oracle's Machine Learning talks, abstracts, downloads and "live" recording below.
Most data science projects don’t get beyond the data scientist and rarely “operationalize” their predictive models. By “moving algorithms to the data,” Oracle now embeds prebuilt analytical machine learning methodologies into applications. This presentation shows how it is done on premises or in the cloud and provides an inventory of current predictive applications, including HCM cloud, sales cloud, retail GBU and FinServ GBU applications, industry data models, and adaptive intelligence applications for manufacturing. Finally, it presents a preview of some new predictive applications in the pipeline. Come away with an understanding of how you too can build machine learning in to your applications.
Link to Recording of "Live" Presentation
at Code One.
In this hands-on lab, learn the fast and easy way to do machine learning with Oracle SQL Developer 18’s Oracle Data Miner drag-and-drop workflow UI. Learn from several experts who will provide one-on-one coaching, guidance, and instruction as requested in various hands-on tutorials. Ask questions, get answers, and come away with a comfort level for using Oracle’s machine learning capabilities in your use cases.
Also try the new Oracle Machine Learning Zeppelin-based notebook for Oracle Autonomous Data Warehouse Cloud. Oracle Machine Learning extends Oracle’s offerings for data science in the cloud, and its collaborative notebook environment helps data scientists build, share, document, and automate data analysis methodologies that run in Oracle Autonomous Data Warehouse Cloud.
Oracle Machine Learning is a web-based notebook application that supports the full range of Oracle’s in-database analytics. It allows business users to create rich, interactive analytical documents. Just like a paper document, each Oracle Machine Learning notebook is based around the concept of paragraphs and each one can run a different SQL statement or query combined with rich markdown-language notations. This session provides a step-by-step guide for setting up Oracle Machine Learning in combination with Oracle Autonomous Data Warehouse Cloud. Come to this session to experience a new, richer way to build documents (reports) against your autonomous data warehouse using all the power of Oracle SQL.
Meet the ML Experts & ML Demo Pod: Oracle’s Machine Learning for the Cloud, Databases, and Big Data with SQL, R, and Notebooks
Oracle provides machine learning (ML) algorithms in Oracle Cloud services, databases, and big data platforms that enable data scientists, citizen data scientists, and application developers to build and deploy predictive models and insights. Oracle’s machine learning Apache Zeppelin notebook with Oracle Data Warehouse Cloud Service provides a collaborative environment for data scientists and a roadmap for Oracle Data Mining, Oracle R Enterprise, the Oracle SQL Developer data miner UI, and Oracle R Advanced Analytics for Hadoop/Spark ML capabilities. By moving algorithms to the data, Oracle Analytics Cloud, BI tools, and applications easily access the ML models and insights. Come to this booth to see demonstrations and talk to Oracle experts in this exciting field of AI and machine learning.
Hope you enjoy!
Please send any questions, comments, suggestions or feedback to firstname.lastname@example.org.
Sr. Director Product Management, Machine Learning, AI and Cognitive Analytics, Oracle