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Oracle Machine Learning Office Hours

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June 22

15:00 - 15:30 UTC    Start Times Around the World

Description

ML Concepts - Encoding of Categorical Attributes: OneHot vs Mean vs WoE and when to use them
Join us on this weekly Office Hours for Oracle Machine Learning on Autonomous Database, where Jie Liu, Data Scientist for Oracle Machine Learning, will cover the different methods of encoding categorical attributes like One-Hot Encoding, Mean Econding and Weight-of-Evidence (WoE), and review the best usage for each of them. He will also present a demo running on a notebook with OML4Py.

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.

Your Experts

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.
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.
Jie Liu
Jie Liu, Data Scientist
Jie Liu is a data scientist. He works with Oracle Machine Learning Product Management team to develop marketing content for OML products and deliver data science solutions for customers inside and outside Oracle. Before joining Oracle, he was a data scientist in Epsilon developing machine learning driven real time bidding strategy and application for online advertisement. He obtained his PhD in Electrical Engineering from University of Notre Dame.

All Sessions

August 11 2021 16:00:00 UTCOracle Machine Learning Office Hours
June 29 2021 15:00:00 UTCHands-on Lab: Machine Learning 101 Classification
June 22 2021 15:00:00 UTCML 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
February 23 2021Hands-On Lab using Oracle Machine Learning for Python on Autonomous Database
February 18 2021Machine Learning 102 - Feature Extraction
December 17 2020Machine Learning 101: Feature Extraction
November 5 2020Machine Learning 102: Clustering
October 28 2020Oracle Machine Learning for R: An Introduction
September 29 2020Machine Learning 101: Clustering
August 4 2020Machine Learning 102: Regression