Oracle Machine Learning for SQL Release 23
Oracle Machine Learning for SQL (OML4SQL) provides a state-of-the-art machine learning capability within Oracle Database. OML4SQL offers a broad set of in-database algorithms for performing machine learning tasks.
Algorithms are implemented as SQL functions and leverage the strengths of Oracle Database. The in-database algorithms perform machine learning on data tables and views, star schema data including transactional data, nested data, aggregations, and unstructured text data.
Algorithms are implemented as SQL functions and leverage the strengths of Oracle Database. The in-database algorithms perform machine learning on data tables and views, star schema data including transactional data, nested data, aggregations, and unstructured text data.
Some administrative tasks that are performed on premises and some key machine learning process tasks are listed here.
Oracle Machine Learning for SQL Tasks
Install and Configure your Database
Install and configure your database for OML4SQL.
Upgrade your Database
Use Database Upgrade Assistant (DBUA) to upgrade your database.
Create a Machine Learning User
Create a database user account to perform machine learning activities.
Export and Import OML4SQL Models
Export and import machine learning models using Oracle Data Pump technology
Prepare Data
Finalize the data and make the data in a format that you can use to build the model.
Create Model
Select and apply various modeling techniques and tune the algorithm parameters.
Score
Apply a model to new data.