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What is Oracle Machine Learning?

Machine learning uncovers hidden patterns and important insights within company data, ultimately providing substantial benefits to organizations. Oracle Machine Learning simplifies the creation and implementation of machine learning models for data scientists by reducing data movement, integrating AutoML capabilities, and making deployment more straightforward. This improvement enhances the productivity of both data scientists and developers while also shortening the learning curve, thanks to the intuitive Apache Zeppelin notebook technology built on open source principles. These notebooks support various programming languages such as SQL, PL/SQL, Python, and markdown tailored for Oracle Autonomous Database, allowing users to work with their preferred programming languages while developing models. In addition, a no-code interface that utilizes AutoML on the Autonomous Database makes it easier for both data scientists and non-experts to take advantage of powerful in-database algorithms for tasks such as classification and regression analysis. Moreover, data scientists enjoy a hassle-free model deployment experience through the integrated Oracle Machine Learning AutoML User Interface, facilitating a seamless transition from model development to practical application. This comprehensive strategy not only enhances operational efficiency but also makes machine learning accessible to a wider range of users within the organization, fostering a culture of data-driven decision-making. By leveraging these tools, businesses can maximize their data assets and drive innovation.

What is Jupyter Notebook?

Jupyter Notebook is a versatile, web-based open-source application that allows individuals to generate and share documents that include live code, visualizations, mathematical equations, and textual descriptions. Its wide-ranging applications include data cleaning, statistical modeling, numerical simulations, data visualization, and machine learning, highlighting its adaptability across different domains. Furthermore, it acts as a superb medium for collaboration and the exchange of ideas among professionals within the data science community, fostering innovation and collective learning. This collaborative aspect enhances its value, making it an essential tool for both beginners and experts alike.

Media

Media

Integrations Supported

Apache Spark
Oracle Database

Integrations Supported

Apache Spark
Betteromics
Coiled
Daivio
Devin Desktop
Edison Analysis
Evidation Health
GeoSpock
Guild AI
Intel Tiber AI Cloud
Modelbit
NVIDIA Morpheus
Spell
Stata
TensorFlow
Thunder Compute
Unfolded
lakeFS
neptune.ai

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Oracle

Date Founded

1977

Company Location

United States

Company Website

www.oracle.com/data-science/machine-learning/

Company Facts

Organization Name

Project Jupyter

Date Founded

2014

Company Website

jupyter.org

Categories and Features

Data Science

Not specified

Machine Learning

Not specified

Categories and Features

Data Science

Not specified

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