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June 15, 2021

15:00 UTC   Start Times Around the World

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Description

OML usage highlight: Machine Learning Recommendations for Maintenance and Repair
This week in our Office Hours for Oracle Machine Learning on Autonomous Database Lee Sacco, Senior Director Depot Repair Development presented the current integrations and usage of Machine Learning from OML in the EBS Depot Repair Application.

The Oracle Machine Learning product family supports data scientists, analysts, developers, and IT to achieve data science project goals faster while taking full advantage of the Oracle platform.

The Oracle Machine Learning Notebooks offers an easy-to-use, interactive, multi-user, collaborative interface based on Apache Zeppelin notebook technology, and support SQL, PL/SQL, Python and Markdown interpreters. It is available on all Autonomous Database versions and Tiers, including the always-free editions.

OML includes AutoML, which provides automated machine learning algorithm features for algorithm selection, feature selection and model tuning, in addition to a specialized AutoML UI exclusive to the Autonomous Database.

OML Services is also included in Autonomous Database, where you can deploy and manage native in-database OML models as well as ONNX ML models (for classification and regression) built using third-party engines, and can also invoke cognitive text analytics.

Video highlights:
01:38 Why NOT start with the Data in Machine Learning
03:55 Starting with the Business Understanding
05:08 What is Oracle EBS Depot Repair?
08:38 User Schema for Repairs
12:18 Structured Data of EBS Depot Repairs
16:40 EBS Depot Repair - Technician Portal
18:42 Oracle Machine Learning recommendations for the Technician
20:53 Automatic Updates to the Technician Portal
21:38 Architecture for ML recommendations - what happens in the back-end?
26:27 Q&A
38:50 Link to a Live Demo

Your Experts

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    Marcos Arancibia

    Marcos Arancibia   

    Marcos Arancibia is a Senior Principal Product Manager in the Oracle Autonomous Database team. He is charted with developing a comprehensive platform for enabling all customers and use cases to be successful on Autonomous Database, and working with developers to bring their Applications and workloads as well. Within Product Management he works to develop product strategy, roadmap prioritization, product positioning and product evangelization, working closely with the engineering teams in defining the product roadmap for Autonomous Database. He previously was a PM for Oracle Machine Learning, and 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.
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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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    Lee Sacco

    Lee Sacco

    Senior Director of Applications Development for Oracle Maintenance Cloud and EBS Depot Repair. 15+ years of experience designing and building enterprise software for maintenance, logistics, CRM, banking and online payments. Currently focused on reliability engineering, failure analytics, and predicting when machines are going to break. Prior to Oracle worked 5 years as a technology integrator for Andersen Consulting. Holds a Bachelor of Science in Symbolic Systems from Stanford University and an MBA from the Swiss Federal Institute of Technology.
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