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Oracle Machine Learning Office Hours

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November 19

17:00 UTC   Start Times Around the World


Introduction to Oracle Machine Learning
In this first Office Hours session for Oracle Machine Learning, Mark Hornick provides an introduction to the Oracle Machine Learning (OML) family of products, both on-premises and on the Oracle Cloud. Learn about the key component technologies and features available today, and that are coming soon. See how the key attributes of automation, scalability, and production readiness enable enterprises to increase productivity, achieve enterprise goals faster, and innovate more.

Oracle Machine Learning consists of complementary components supporting scalable machine learning algorithms for in-database and big data environments (including Cloud and on-premises), notebook technology, SQL, Python and R APIs, and Hadoop/Spark environments.

Video highlights:

00:20 - Oracle Machine Learning Key Attributes
03:00 - OML components rebranding
04:40 - OML empowers Enterprise Users
09:55 - Cross-Platform Machine Learning
13:40 - OML Notebooks and OML4SQL
21:50 - OML4R and OML4Python
33:20 - AutoML with OML4Py
37:17 - OML4Spark
39:27 - Application Integration with OML
41:10 - OML Roadmap
50:38 - Q&A

Full set of slides available as the first link in the Resources below.

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Your Experts

Mark Hornick
Mark Hornick, Senior Director, Product Management, Data Science and Machine Learning    
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, working with internal and external customers in the application of Oracle’s machine learning technologies for scalable and deployable data science projects. Mark is Oracle’s representative on the R Consortium’s Board of Directors, an Oracle Adviser and founding member of the Business Intelligence Warehousing and Analytics (BIWA) User Community, and Content Selection Committee Chair for the Analytics and Data Summits.
Marcos Arancibia
Marcos Arancibia, Product Manager, Data Science and Big Data    
Marcos Arancibia is the Product Manager for Oracle Data Science and Big Data. He works with Machine Learning in the Oracle Database and on Big Data clusters under Hadoop and Spark, on premises and in the Oracle Cloud. He works within Product Management to develop product strategy, roadmap prioritization, product positioning and product evangelization, working closely with the engineering team in defining the product roadmaps for Oracle Machine Learning and Big Data in the Cloud. Before joining Oracle 9 years ago he was at SAS Institute Inc. for 13 years as a Data Mining architect and expert in the US and Latin America. He holds a Bachelor Degree of Science in Statistics with additional courses in the Master of Science in Statistics, both from UNICAMP in Brazil. He has Certifications from Stanford on AI and Machine Learning, and from the University of Washington on Computational Neuroscience. He is an expert on Deep Learning and passionate about Machine Learning.
Charlie Berger
Charlie Berger, Sr. Director Product Management, Machine Learning, AI and Cognitive Analytics    
Charlie Berger is the Sr. Director of Product Management, Machine Learning, AI and Cognitive Analytics in Oracle Server Technology. He’s been carrying the Product Management flag for Oracle’s server tech machine learning for 20 years—starting when Oracle acquired Thinking Machines Corporation’s data mining development team where he was the VP of Product Management. He is a technical evangelist and supports Application Dev. teams who embed ML, supports customers and Sales and is the co-founder of the (BIWA) Analytics and Data Summit events. Previously, he worked in startups in expert systems, statistical and data visualization software and robotics and machine vision. He holds a Master of Science in Manufacturing Engineering and an MBA, both from Boston University. He holds a BS in Operations Research/Industrial Engineering from UMASS, Amherst.