Using Oracle Machine Learning with Autonomous Database 2024 ELS

• Table of
• Lesson 1: Oracle Machine Learning – Overview
• Cloud-Based Solutionfor Analytics
• El Tronics
• Oracle Autonomous Database
• Basic Machine Learning Flow
• OML: Introduction
• Machine Learning: Horizontal Use Cases
• Use Cases and Machine Learning Techniques
• Industry: Vertical Use Cases
• Lesson 2: Features
• Components
• Oracle Machine Learning
• Steps in the ML process
• Lesson 3: Introduction to Machine Learning for Python
• Oracle Machine Learningfor Python
• Features
• Advantages
• Lesson 4: Introduction to Machine Learning for R
• Features
• Advantages

Lesson 5: Creating Workspaces and Projects for use with OML Notebooks and AutoML UI

• Terry’s Business Problem
• El Tronics
• Accessing the Oracle Machine Learning Home Page
• Creating a New Project and Workspace
• Creating a New Project
• Selecting the New Project
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• Using Oracle Machine Learning with Autonomous Database – 2024 3
• Creating a Workspace
• Lesson 6: Users in Workspaces in Oracle Machine Learning
• Managing Workspaces
• Workspace Permissions
• Workspace Permissions Types
• Workspace Permissions
• Moving a Project to a Different Workspace
• Lesson 7: Using the OML Scratchpad Notebook
• Scratchpad Notebooks
• Developing Code
• Simple SQL Queryin Scratchpad
• Example 1
• Example 2
• Exporting and Importing Notebooks
• Exporting a notebook: Example
• Lesson 8: Restrictions on SQL Commands
• Restrictions for Database Options
• Restrictions for Database Initialization Parameters
• Modifiable Initialization Parameters
• Lesson 9: Introduction to AutoML in Oracle Machine Learning
• Introduction to AutoML
• AutoML in OML4Py
• The OML AutoML UI Pipeline
• Algorithm Selection
• Feature Selection
• Model Tuning
• Lesson 10: AutoML with OML4Py
• AutoML in OML4Py
• Importing AutoML and Creating the DataFrame
• Algorithm Selection with OML4Py
• Algorithm Ranking with OML4Py: Example
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• Using Oracle Machine Learning with Autonomous Database – 2024 4
• Feature Selection with OML4Py
• Feature Selection with OML4Py: Example
• Model Tuning with OML4Py
• Model Tuning with OML4Py: Example
• Model Selection with OML4Py
• Model Selection with OML4Py: Example
• Lesson 11: OML AutoML User Interface (UI)
• OML AutoML UI Experiment Pipeline
• OML AutoML UI Features
• Creating an AutoML UI Experiment
• Oracle Machine Learning Home Page: AutoML
• Creating an AutoML UI Experiment: Example
• Viewing AutoML Experiment Classification Metrics
• Deploying the AutoML Model
• Generating a notebook for the AutoML Model
• Creating a Notebook from the AutoML Model: Example
• Lesson 12: Notebooks
• Creating a Notebook
• OML Notebooks: Example
• Creating a Notebook
• Editing a Notebook
• Running a Notebook
• Lesson 13: Forms in Notebooks
• Creating Text Input Forms in Notebooks
• Creating Text Input Forms in Notebooks: Example
• Creating Select Forms in Notebooks
• Creating Select Forms in Notebooks: Example
• Creating Check Box Forms in Notebooks
• Creating Check Box Forms in Notebooks: Example
• Output Formats Supported by the SET SQLFORMAT Command
• Lesson 14: Versioning in Notebooks
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• Using Oracle Machine Learning with Autonomous Database – 2024 5
• Versions of a Notebook
• Creating Multiple Versions of a Notebook
• Restore Version of a Notebook
• Creating Multiple Versions of a Notebook
• Lesson 15: Templates
• Templates Home Page
• Sharing a notebook by using Oracle Machine Learning templates
• Saving a notebook as a template in Oracle Machine Learning
• Personal Templates
• Lesson 16: Instantiating Notebooks from Templates
• Creating Notebooks from Templates
• Sharing Templates
• Sharing Templates: Example
• Editing Template Settings
• Shared Templates
• Shared Templates: Example
• Example Templates
• Example Templates: Example
• Lesson 17: Working with Jobs
• Objectives
• Jobs
• Oracle Machine Learning Jobs: Example
• Creating a Job
• Creating a Job: Example
• Viewing Job Logs
• Lesson 18: OML Data Monitoring User Interface (UI)
• Value of Data Monitoring
• Data Monitoring
• Data Drift
• Data Drift: Overall Metric
• Creating a Data Monitor
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• Using Oracle Machine Learning with Autonomous Database – 2024 6
• Oracle Machine Learning Home Page: AutoML
• Creating a Data Monitor: Example
• Data Drift: Feature Statistics
• Individual Feature Statistics
• Lesson 19: OML Model Monitoring User Interface (UI)
• Value of Model Monitoring
• Example Use Cases
• Concept Drift
• Model Monitoring
• Creating a Model Monitor
• Oracle Machine Learning Home Page: Model Monitors
• Creating a Model Monitor: Example
• Model Monitor Results: Model Drift
• Model Monitor Results: Metric
• Prediction Statistics
• Model Monitor Details: Feature Impact
• Model Monitor Details
• Lesson 20: Administering Oracle Machine Learning
• Administering OracleMachine Learning
• Workflow for Managing Oracle Machine Learning
• User Data
• User Data: Example1
• User Data: Example2
• Compute Resource
• Compute Resource: Example
• Creating User Accounts for Oracle Machine Learning
• Creating User Accounts for Oracle Machine Learning: Example
• Lesson 21: Connection Groups