Data scientists and developers know the power of Python and Python's wide-spread adoption is a testament to its success. Now, Python users can extend this power when analyzing data in Oracle Autonomous Database. Oracle Machine Learning for Python (OML4Py) makes the open source Python scripting language and environment ready for the enterprise and big data.
Designed for problems involving both large and small data volumes, Oracle Machine Learning for Python integrates Python with Oracle Autonomous Database, allowing users to run Python commands and scripts for data exploration, statistical analysis, and machine learning on database tables and views using Python syntax. Familiar Python functions are overloaded to translate Python functionality into SQL for in-database processing - achieving performance and scalability - transparently.
Python users can take advantage of parallelized in-database algorithms to enable scalable model building and data scoring - eliminating costly data movement. Further, Python users can develop and deploy user-defined Python functions that leverage the parallelism and scalability of Autonomous Database, and deploy those same user-defined Python functions using environment-managed Python engines through a REST API.
Oracle Machine Learning for Python also introduces automated machine learning (AutoML), which consists of: automated algorithm selection to select the algorithm most appropriate for the provided data, automated feature selection to enhance model accuracy and performance, and automated model tuning to improve model quality. AutoML enhances data scientist productivity by automating repetitive and time-consuming tasks, while also enabling non-experts to produce models without needing detailed algorithm-specific knowledge.
Access Oracle Machine Learning for Python in Autonomous Database using Oracle Machine Learning Notebooks, where you can use Python and SQL in the same Apache Zeppelin-based notebook - allowing the most appropriate API for the task. Take advantage of team collaboration and job scheduling features to further your data science project goals.
Oracle Machine Learning for Python has a range of template example notebooks included with Oracle Autonomous Database that highlight various features. Zeppelin notebooks illustrating OML4Py features are also available in the Oracle Machine Learning GitHub repository.