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October 28

15:00 UTC   Start Times Around the World

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Oracle Machine Learning for R: An Introduction
Join us for a look at Oracle Machine Learning for R (OML4R) – the R interface to in-database machine learning and R script deployment from Oracle. R is the top statistical programming language for data science and computational statistics.

OML4R enables you to work with database tables and views using familiar R syntax and functions. For scalable and performant data exploration, data preparation, and machine learning, leverage Oracle Database as a high performance compute engine. Build machine learning models using parallelized in-database algorithms using R Formula-based specification.

Invoke user-defined R functions from SQL for deployment in applications and dashboards, where R engines are dynamically spawned and controlled by Oracle Database. Even take advantage of running your R functions in a data-parallel and task-parallel manner.

We’ll include a demonstration of OML4R that takes us through the transparency layer, in-database machine learning, and embedded R execution functionality.

Video highlights:
01:08 Oracle Machine Learning Office Hours - next Session
02:24 Oracle Machine Learning for R: an Introduction
03:40 Machine Learning Pain Points
04:06 Oracle Machine Learning
05:16 Oracle Machine Learning for SQL
06:11 Traditional Analytics and data source interaction
07:35 Oracle Machine Learning for R
09:45 Proxy objects
10:25 Data types
10:56 OML4R Algorithms
11:35 Scalable Data Analysis - Model Building
14:06 Demo - OML4R Tour in RStudio
18:15 Demo - OML4R overloaded dplyr
18:49 Demo - OML4R Join Data tables
19:50 Demo - OML4R overloaded graphic functions
20:17 Demo - OML4R Machine Learning classification
23:20 Demo - OML4R Embedded R execution
25:13 Demo - OML4R Embedded R execution from SQL Developer
29:34 Demo - OML4R groupApply
31:20 R Consortium
32:07 Why Oracle for Machine Learning with R?
33:35 Q&A

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, Senior Principal Product Manager, Machine Learning    
Marcos Arancibia is the Product Manager for Oracle Machine Learning, working with Machine Learning in the Oracle Database and on Spark. He develops product strategy, roadmap prioritization, product positioning and product evangelization, helping define the product roadmap for Oracle Machine Learning. 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.

All Sessions

November 2 2021 15:00:00 UTCWeekly Office Hours: OML on Autonomous Database - Ask & Learn
October 12 2021 15:00:00 UTCOML feature highlight: Time Series analysis with Oracle Machine Learning
October 5 2021 15:00:00 UTCOML4Py: Using third-party Python packages from Python, SQL and REST
September 28 2021 15:00:00 UTCWeekly Office Hours: OML on Autonomous Database - Ask & Learn
September 21 2021 15:00:00 UTCOML usage highlight: Live Demo of Oracle Stream Analytics with OML AutoML UI and OML Services
August 17 2021OML Usage Highlight: ML on SailGP data: Predicting the best sailing direction
August 10 2021OML feature highlight: Deploy an XGBoost Model using OML Services
August 3 2021ML Concepts - Using Cross-Validation with OML in-Database and with Embedded Python Execution
June 29 2021Weekly Office Hours: OML on Autonomous Database - Ask & Learn
June 22 2021ML Concepts - Encoding of Categorical Attributes: OneHot vs Mean vs WoE and when to use them
June 15 2021OML usage highlight: Machine Learning Recommendations for Maintenance and Repair
May 25 2021Hands-On Lab using Oracle Machine Learning AutoML UI on Autonomous Database
May 18 2021Hands-On Lab using Oracle Machine Learning Services on Autonomous Database
May 11 2021OML usage highlight: Oracle Process Automation with Real-time OML Services scoring
April 20 2021OML usage highlight: Oracle Stream Analytics with Real-time OML Services scoring
April 13 2021OML usage highlight: Making Oracle Digital Assistant smarter with OML Services
March 30 2021OML feature highlight: OML AutoML UI for Automated Model Building
March 23 2021Weekly Office Hours: OML on Autonomous Database - Ask & Learn
March 11 2021OML feature highlight: OML Services on Autonomous for Model Deployment
March 2 2021Weekly Office Hours: OML on Autonomous Database - Ask & Learn