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March 11, 2021

16:00 UTC   Start Times Around the World

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Description

OML feature highlight: OML Services on Autonomous for Model Deployment
We learned about and saw a live demo of a new feature of Oracle Machine Learning on Autonomous Database: Oracle Machine Learning Services.

OML Services extends OML functionality to support model deployment and model lifecycle management for both in-database OML models and third-party Open Neural Networks Exchange (ONNX) machine learning models via REST APIs.

The REST API for Oracle Machine Learning Services provides REST API endpoints hosted on Oracle Autonomous Database. These endpoints enable the storage of machine learning models along with its metadata, and the creation of scoring endpoints for the model.

These third-party classification or regression models can be built using tools that support the ONNX format, which includes packages like Scikit-learn and TensorFlow, among several others.

In addition, OML Services supports proprietary cognitive text capabilities, with capabilities for topic discovery, keywords, summary, sentiment, and feature extraction. The initial languages supported include English, Spanish, and French (based on a Wikipedia knowledgebase using embeddings).

OML Services cognitive image functionality, supported through the ONNX format third-party model deployment feature, supports scoring using images or tensors.

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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    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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