Table of Contents

• Title and Copyright Information
• Preface
  • Audience
  • Conventions
  • Documentation Accessibility
  • Related Resources
• 1 What's New
• 2 Get Started
  • 2.1 Get Started with Oracle Machine Learning User Interface
  • 2.2 Access Oracle Machine Learning User Interface
    • 2.2.1 About Oracle Machine Learning Password Policy
  • 2.3 Oracle Machine Learning User Interface Home Page
  • 2.4 Oracle Machine Learning Notebooks
    • 2.4.1 Typical Actions when Using Oracle Machine Learning Notebooks
  • 2.5 GitHub Notebooks
  • 2.6 AutoML UI
  • 2.7 Data Monitoring
  • 2.8 Model Monitoring
• 3 Project and Workspaces
  • 3.1 Create Projects
  • 3.2 Create and Manage Workspaces and Projects
  • 3.3 Grant Workspace Permissions
    • 3.3.1 About Workspace Permission Types
• 4 OML Notebooks
  • 4.1 Oracle Machine Learning Notebooks
    • 4.1.1 Access your Oracle Machine Learning Notebooks
    • 4.1.2 Edit your Oracle Machine Learning Notebook
      • 4.1.2.1 Work with Notebook Versions in the Notebook Editor
      • 4.1.2.2 Create Paragraph Dependencies
    • 4.1.3 Manage Oracle Machine Learning Notebooks
      • 4.1.3.1 Work with Notebook Versions on the Notebooks Page
  • 4.2 GitHub Notebooks
    • 4.2.1 Create GitHub Credentials
      • 4.2.1.1 Generate Personal Access Token
    • 4.2.2 Clone and Access your GitHub Notebook
    • 4.2.3 Edit and Sync your GitHub Notebook
    • 4.2.4 Manage GitHub Notebooks
  • 4.3 Enable GPU Compute Capabilities in a Notebook through the Python Interpreter
  • 4.4 Visualize your Data in Oracle Machine Learning Notebooks
    • 4.4.1 Visualize Data in a Table
    • 4.4.2 Visualize Data in a Bar Chart
    • 4.4.3 Visualize Data in a Funnel Chart
    • 4.4.4 Visualize Data in a Pyramid Chart
    • 4.4.5 Visualize Data in a Scatter Plot
    • 4.4.6 Visualize Data in a Line Chart
    • 4.4.7 Visualize Data in an Area Chart
    • 4.4.8 Visualize Data in a Pie Chart
    • 4.4.9 Visualize Data in a Box Plot
    • 4.4.10 Visualize your Data in a Sunburst Chart
    • 4.4.11 Visualize your Data in a Tag Cloud
    • 4.4.12 Visualize your Data in a Treemap
    • 4.4.13 Visualize Data in a Map
  • 4.5 Export a Notebook
  • 4.6 Import a Notebook
  • 4.7 Use the SQL Interpreter in a Notebook Paragraph
    • 4.7.1 About Oracle Machine Learning for SQL
    • 4.7.2 Set Output Format in Notebooks
    • 4.7.3 Output Formats Supported by SET SQLFORMAT Command
  • 4.8 Use the Python Interpreter in a Notebook Paragraph
    • 4.8.1 About Oracle Machine Learning for Python
  • 4.9 Use the R Interpreter in a Notebook Paragraph
    • 4.9.1 About Oracle Machine Learning for R
  • 4.10 Use the Conda Interpreter in a Notebook Paragraph
    • 4.10.1 About the Conda Environment and Conda Interpreter
    • 4.10.2 Conda Interpreter Commands
    • 4.10.3 Create a Conda Environment for Python, Install a Python Package and Upload it to Object Storage
    • 4.10.4 Create a Conda Environment for R and Install R Package and Upload it to Object Storage
    • 4.10.5 Upload the Conda environments to an Object Storage bucket associated with the Autonomous AI Database
  • 4.11 Use the Scratchpad
  • 4.12 Use the Markdown Interpreter and Generate Static html from Markdown Plain Text
  • 4.13 About Interpreters and Notebook Service Levels
    • 4.13.1 Change Notebook Service Level
    • 4.13.2 Verify Notebook Service Level
• 5 AutoML UI
  • 5.1 Access AutoML UI
  • 5.2 Create AutoML UI Experiment
    • 5.2.1 Supported Data Types for AutoML UI Experiments
  • 5.3 View an Experiment
    • 5.3.1 Create Notebooks from AutoML UI Models
• 6 Data Monitoring
  • 6.1 Create a Data Monitor
  • 6.2 View Data Monitor Results
  • 6.3 View History
• 7 Model Monitoring
  • 7.1 Create a Model Monitor
  • 7.2 View Model Monitor Results
  • 7.3 View Model History
• 8 Models
  • 8.1 Deploy Model
• 9 Templates
  • 9.1 Use the Personal Templates
    • 9.1.1 Create Notebooks from Templates
    • 9.1.2 Share Notebook Templates
    • 9.1.3 Edit Notebook Templates Settings
  • 9.2 Use the Shared Templates
    • 9.2.1 Create Notebooks from Templates
    • 9.2.2 Edit Notebook Templates Settings
  • 9.3 Use the Example Templates
    • 9.3.1 Create a Notebook from the Example Templates
    • 9.3.2 Example Templates
• 10 Jobs
  • 10.1 About Jobs
  • 10.2 Create Jobs to Schedule Notebooks
  • 10.3 View Job Logs
• 11 Admin
  • 11.1 Typical Workflow for Managing Oracle Machine Learning
  • 11.2 Access OML User Management from Command Line
    • 11.2.1 Obtain URLs for OML User Management, REST API for OML Services, REST API for OML4Py and OML4R embedded execution from Command Line or the Autonomous AI Database
  • 11.3 Manage OML Users and User Accounts
    • 11.3.1 Add Existing Database User Account to Oracle Machine Learning Components
  • 11.4 About User Data
    • 11.4.1 Reassign
  • 11.5 About Compute Resource
    • 11.5.1 Oracle Resource
      • 11.5.1.1 Resource Services and Notebooks
  • 11.6 Get Started with Connection Groups
    • 11.6.1 About Connection Groups
    • 11.6.2 About Global Connection Group
    • 11.6.3 Edit Oracle AI Database Interpreter Connection
  • 11.7 Get Started with Notebook Sessions
• A.1 FAQs
  • A.1.1 How to grant access to an OML model by giving global or selective access to other users?
  • A.1.2 How to obtain the URL for REST API for OML Services, REST API for OML4Py and OML4R embedded execution from the Autonomous AI Database ?
  • A.1.3 How to push content represented by an OML proxy object into a table in the Oracle Autonomous AI Database?
  • A.1.4 What is the expected behavior if the embedded REST execution requests surpass the capacity of the VM?
  • A.1.5 Who owns and manages the VMs on which embedded Python execution is downloaded?
  • A.1.6 Where can I find the list of all the functions available in the oml python package?
  • A.1.7 What is the difference between the OML ECPUs and the Database ECPUs?
  • A.1.8 What is an alternative solution to oml.connect() for Oracle Machine Learning solutions deployment?
  • A.1.9 What other models can I host on OML besides the in-database models?
  • A.1.10 Does Oracle Machine Learning support reading of data from OCI Streaming services or Kafka?
  • A.1.11 How can I create a Conda environment for Python and R, install packages and upload the environment in a single step
• A.2 Troubleshooting
  • A.2.1 OML4Py
    • A.2.1.1 Error when importing matplotlib
    • A.2.1.2 Error when importing Python interpreters
    • A.2.1.3 How to add HostAce using cursor in Python?
    • A.2.1.4 Error when installing OML4Py Server for On-Premises Oracle AI Database
  • A.2.2 OML4R
    • A.2.2.1 How to add rows to a table in the database through an ore.frame
    • A.2.2.2 Unable able to push an object to Autonomous AI Lakehouse from an Oracle Machine Learning Notebook session using OML4R equivalent of OML4Py
  • A.2.3 OML Notebooks
    • A.2.3.1 How to install third-party packages for both Python and R in Oracle Machine Learning Notebooks
    • A.2.3.2 How to upload data from a .csv file into a Pandas DataFrame
    • A.2.3.3 "Allow Run" button to warn users about potential security threat
    • A.2.3.4 Resource Management in Oracle Machine Learning
  • A.2.4 Conda
    • A.2.4.1 Error when loading libraries in Conda environments in Oracle Machine Learning Notebooks