OML4Py features: Using third-party Python packages from Python, SQL and REST
Join us on this Office Hours for Oracle Machine Learning on Autonomous Database, where Sherry LaMonica, Principal Member of Technical Staff at Oracle Machine Learning team will explain how to use third-party Python packages from Python, SQL and REST via OML4Py.
So you want to deploy your Python scripts to production in the database environment. With Oracle Machine Learning for Python, you can invoke user-defined functions on database-spawned and controlled Python engines using embedded Python execution. An added benefit is the ability to easily leverage data-parallel and task-parallel invocation aided by the database environment. Join this session to learn about the options for working with third-party packages with OML4Py, both on premises and in Autonomous Database, from the Python, SQL and REST APIs.
The Oracle Machine Learning product family supports data scientists, analysts, developers, and IT to achieve data science project goals faster while taking full advantage of the Oracle platform.
01:05 Goals for today
01:24 Third-Party Packages
02:02 Should I use a third-party Python Package on database data?
03:05 Performance characteristics for open-source Python packages with Embedded Python Execution
03:47 Which third-party packages can be used with OML4Py
04:27 Package Management - using pip
05:29 Package Management - using virtualenv
06:45 Embedded Python Execution - Introduction
08:05 Embedded Python Execution - Benefits
09:02 OML4Py Interfaces for Embedded Python Execution
09:26 Embedded Python Execution - functions via Python and SQL
10:58 Embedded Python Execution - functions via REST interface
11:25 Which OML4Py interface should I use for Embedded Python Execution?
12:09 Script Repository and datastore
13:11 Functions for managing scripts
13:54 OML4Py Datastore
14:45 Functions for managing datastore objects
15:26 Parallelism
16:43 Parallelism - Embedded Python Execution - Python interface
17:21 Parallelism - Embedded Python Execution - SQL interface
17:52 Interfaces for Embedded Python Execution - Python
18:30 Interfaces for Embedded Python Execution - SQL
19:08 Interfaces for Embedded Python Execution - REST
20:08 Demo
28:29 Q&A
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