Oracle Machine Learning

Apache Zeppelin based Machine Learning SQL Notebook for Data Scientists to Collaborate in the Oracle Autonomous Data Warehouse

Overview

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Oracle Machine Learning is a SQL notebook interface for data scientists to perform machine learning in the Oracle Autonomous Data Warehouse (ADW). 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 SQL notebooks, based on Apache Zeppelin technology, enable teams to collaborate to build, evaluate and deploy predictive models and analytical methodologies in the Oracle ADW. 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 SQL notebooks provide easy access to Oracle's parallelized, scalable in-database implementations of a library of Oracle Advanced Analytics' machine learning algorithms (classification, regression, anomaly detection, clustering, associations, attribute importance, feature extraction, times series, etc.), SQL, PL/SQL and Oracle's statistical and analytical SQL functions. Oracle Machine Learning SQL notebooks and Oracle Advanced Analytics' library of machine learning SQL functions combined with PL/SQL 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 SQL notebooks adhere to all Oracle standards and supports privilege-based access to data, models, and notebooks.  

 

Key Features

  • Collaborative SQL notebook UI for data scientists  
  • Packaged with Oracle Autonomous Data Warehouse
  • Easy access to shared notebooks, templates, permissions, scheduler, etc.
  • Access to 30+ parallel, scalable in-database implementations of machine learning algorithms
  • SQL and PL/SQL scripting language supported
  • Enables and Supports Deployments of Enterprise Machine Learning Methodologies in ADW

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