The following topics describe Oracle Machine Learning for Python (OML4Py) and its advantages for the Python user.

• What Is Oracle Machine Learning for Python
  Oracle Machine Learning for Python (OML4Py) enables you to run Python commands for data transformations and for statistical, machine learning, and graphical analysis on data stored in or accessible through an Oracle database using a Python API. The OML4Py supports running user-defined Python functions through the database spawned and controlled Python engines, with optional built-in data-parallelism and task-parallelism. This embedded execution functionality enables invoking user-defined functions from SQL, and on ADB, REST. The OML4Py supports Automated Machine Learning (AutoML) for algorithm and feature selection, and model tuning and selection. You can augment the Python included functionality with third-party packages from the Python ecosystem.
• Advantages of Oracle Machine Learning for Python
  Using OML4Py to prepare and analyze data in or accessible to an Oracle database has many advantages for a Python user.
• Manipulate database tables and views using familiar Python functions and syntax
  With the transparency layer classes, you can manipulate database tables and views using familiar Python functions and syntax, For example, using DataFrame proxy objects that map to database data, users can invoke overloaded Pandas functions that transparently generate SQL that runs in the database, using the database as a high-performance compute engine.
• About the Python Components and Libraries in OML4Py
  OML4Py requires an installation of Python, the specified Python libraries, as well as the OML4Py components.