Oracle Machine Learning provides a new notebook interface for data scientists to perform machine learning in Oracle Autonomous Database. Notebook technologies support the creation of scripts while supporting the documentation of assumptions, approaches and rationale to increase data science team productivity. Oracle Machine Learning Notebooks, based on Apache Zeppelin technology, enable teams to collaborate to build, evaluate and deploy predictive models and analytical methodologies in the Oracle Database. Multi-user collaboration enables the same notebook to be opened simultaneously by different users. Changes made by one user are immediately updated for other team members.
Oracle Machine Learning Notebooks provide easy access to Oracle's parallelized, scalable in-database implementations of a library of Oracle Machine Learning algorithms (classification, regression, anomaly detection, clustering, associations, attribute importance, feature extraction, times series, etc.) and Oracle's statistical and analytical SQL functions. Oracle Machine Learning notebooks and Oracle Machine Learning's library ML functions allow companies to automate their discovery of new insights, generate predictions and add "AI" to data viz dashboards and enterprise applications.
To support enterprise requirements for security, authentication, and auditing, Oracle Machine Learning Notebooks adhere to all Oracle standards and supports privilege-based access to data, models, and notebooks.
Disclaimer: Product details/functionality subject to change.
Oracle Machine Learning enables data science teams to collaboratively build machine learning methodologies in the Oracle Autonomous Database.
OML Notebooks provide easy access to data managed in Oracle Autonomous Database for quick analysis, simple visualizations and building machine learning solutions.
Oracle Machine Learning notebook starting page.
Create a new Oracle Machine Learning notebook.
Create simple visualizations of data managed in Oracle Autonomous Database.
Easily perform quick statistical analyses using Oracle's in-database statistical functions.
Build, evaluate and deploy machine learning models inside the Oracle Autonomous Database.