Upgrade to Pro — share decks privately, control downloads, hide ads and more …

ML Concepts - Using Cross-Validation with OML i...

ML Concepts - Using Cross-Validation with OML in-Database and with Embedded Python Execution

On this weekly Office Hours for Oracle Machine Learning on Autonomous Database, Jie Liu, Data Scientist for Oracle Machine Learning, will cover Cross-Validation methods, why they are useful and how to run it using in-Database methods using OML and also Embedded Python Execution open-source methods. 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.

Marcos Arancibia

August 03, 2021
Tweet

More Decks by Marcos Arancibia

Other Decks in Technology

Transcript

  1. Oracle Machine Learning Office Hours Weekly Session – Ask &

    Learn with Marcos Arancibia, Sherry LaMonica & Mark Hornick Product Management, Oracle Machine Learning July 2021 This Session will be Recorded
  2. • Upcoming Notebook Template Enhancements • Q&A Topics for today

    Copyright © 2021, Oracle and/or its affiliates 2
  3. Helpful Links 3 ORACLE MACHINE LEARNING ON O.COM https://www.oracle.com/machine-learning OML

    TUTORIALS OML LiveLab: https://apexapps.oracle.com/pls/apex/dbpm/r/livelabs/view-workshop?p180_id=560 OML4Py LiveLab: https://apexapps.oracle.com/pls/apex/dbpm/r/livelabs/view-workshop?wid=786 Interactive tour: https://docs.oracle.com/en/cloud/paas/autonomous-database/oml-tour OML OFFICE HOURS https://asktom.oracle.com/pls/apex/asktom.search?office=6801#sessionss ORACLE ANALYTICS CLOUD https://www.oracle.com/solutions/business-analytics/data-visualization/examples.html OML4PY ORACLE AUTOML UI OML SERVICES Oracle Machine Learning AutoML UI (2m video) Oracle Machine Learning Demonstration (6m video) OML AutoML UI Technical Brief Blog: Introducing Oracle Machine Learning AutoML UI Oracle Machine Learning Services (2m video) OML Services Technical Brief Oracle Machine Learning Services Documentation Blog: Introducing Oracle Machine Learning Services GitHub Repository with OML Services examples OML4Py (2m video) OML4Py Introduction (17m video) OML4Py Technical Brief OML4Py User’s Guide Blog: Introducing OML4Py GitHub Repository with Python notebooks
  4. On our GitHub, you can find: Copyright © 2021, Oracle

    and/or its affiliates 4 github.com/oracle/oracle-db-examples/tree/master/machine-learning • Example Notebooks in OML4SQL and OML4Python • SQL code examples for DB 18c, 19c and 21c • Labs folder with OML4Py HOL Labs • OML Services demos including Cognitive Text Demos, in PostMan collections