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OML feature highlight: New OML Notebook templates for ML Feature Extraction

In this weekly Office Hours for Oracle Machine Learning on Autonomous Database, we introduced the latest Notebook templates for Machine Learning Feature Extraction problems. This was a follow-along Session, since the OML Notebook templates are available to any Autonomous Database tenancy, and people were able to run it while we demonstrated it. Video Highlights: 00:52 Topics for Today 01:26 Upcoming Sessions 01:58 Upcoming Sessions listing 02:28 Feature Extraction Algorithms 05:00 Attribute Importance 05:37 OML Attribute Importance 06:20 Singular Value Decomposition - SVD 07:10 Oracle Machine Learning SVD implementation 07:40 Non-negative Matrix Factorization - NMF 08:32 Two options to access the Template Examples 11:23 Live demo and follow-along for Feature Extraction examples 10:29 Demo of OML4Py Attribute Importance MDL 15:37 Demo of OML4SQL Feature Importance Unsupervised Attribute Importance 18:21 Demo of OML4Py Dimensionality Reduction SVD 25:16 Demo of OML4SQL Dimensionality Reduction NMF 27:08 Q&A

Resources

Featured Speakers

  • Speaker

    Marcos Arancibia

    Oracle
    Senior Principal Product Manager, Autonomous Database

  • Speaker

    Mark Hornick

    Oracle
    Senior Director, Product Management, Machine Learning and AI

  • Speaker

    SHERRY LAMONICA


    Consulting Member of Technical Staff, Oracle Machine Learning Product Management

Workshop Info

Session Has Completed - 18 January 2022
30 Minutes
Oracle Machine Learning Office Hours
English
Oracle Machine Learning