Chapter 6 Train and Use Machine Learning Models

Table of Contents

6.1 About MySQL HeatWave AutoML

6.1.1 MySQL HeatWave AutoML Ease of Use

6.1.2 MySQL HeatWave AutoML Workflow

6.1.3 MySQL HeatWave AutoML Learning Types

6.1.4 Oracle AutoML

6.2 Additional MySQL HeatWave AutoML Requirements

6.3 MySQL HeatWave AutoML Privileges

6.4 Supported Data Types for MySQL HeatWave AutoML

6.5 Create a Machine Learning Model

6.5.1 Prepare Data

6.5.2 Train a Model

6.5.3 Load a Model

6.5.4 Generate Predictions

6.5.5 Generate Model Explanations

6.5.6 Generate Prediction Explanations

6.5.7 Score a Model

6.6 Learn About MySQL HeatWave AutoML with Oracle Cloud Infrastructure Generative AI

6.7 Machine Learning Use Cases

6.7.1 Classify Data

6.7.2 Perform Regression Analysis

6.7.3 Generate Forecasts

6.7.4 Detect Anomalies

6.7.5 Generate Recommendations

6.7.6 Topic Modeling

6.8 Use MySQL HeatWave AutoML with Lakehouse

6.9 Manage Machine Learning Models

6.9.1 The Model Catalog

6.9.2 Work with Model Handles

6.9.3 Unload a Model

6.9.4 View Model Details

6.9.5 Delete a Model

6.9.6 Share a Model

6.9.7 Manage External ONNX Models

6.9.8 Analyze Data Drift

6.10 Track Progress for MySQL HeatWave AutoML Routines

6.11 Monitor the Status of MySQL HeatWave AutoML

This chapter describes how to create and manage machine learning models with MySQL HeatWave AutoML.