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ease
features
design
support

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Description

MLReef allows domain specialists and data scientists to collaborate securely through a blend of coding and no-coding methods. This results in a remarkable 75% boost in productivity, as teams can distribute workloads more effectively. Consequently, organizations are able to expedite the completion of numerous machine learning projects. By facilitating collaboration on a unified platform, MLReef eliminates all unnecessary back-and-forth communication. The system operates on your premises, ensuring complete reproducibility and continuity of work, allowing for easy rebuilding whenever needed. It also integrates with established git repositories, enabling the creation of AI modules that are not only explorative but also versioned and interoperable. The AI modules developed by your team can be transformed into user-friendly drag-and-drop components that are customizable and easily managed within your organization. Moreover, handling data often necessitates specialized expertise that a single data scientist might not possess, making MLReef an invaluable asset by empowering field experts to take on data processing tasks, which simplifies complexities and enhances overall workflow efficiency. This collaborative environment ensures that all team members can contribute to the process effectively, further amplifying the benefits of shared knowledge and skill sets.

Description

Machine learning reveals concealed patterns and valuable insights within enterprise data, ultimately adding significant value to businesses. Oracle Machine Learning streamlines the process of creating and deploying machine learning models for data scientists by minimizing data movement, incorporating AutoML technology, and facilitating easier deployment. Productivity for data scientists and developers is enhanced while the learning curve is shortened through the use of user-friendly Apache Zeppelin notebook technology based on open source. These notebooks accommodate SQL, PL/SQL, Python, and markdown interpreters tailored for Oracle Autonomous Database, enabling users to utilize their preferred programming languages when building models. Additionally, a no-code interface that leverages AutoML on Autonomous Database enhances accessibility for both data scientists and non-expert users, allowing them to harness powerful in-database algorithms for tasks like classification and regression. Furthermore, data scientists benefit from seamless model deployment through the integrated Oracle Machine Learning AutoML User Interface, ensuring a smoother transition from model development to application. This comprehensive approach not only boosts efficiency but also democratizes machine learning capabilities across the organization.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Hive
Apache Spark
Docker
Impala
Keras
Kinetica
MXNet
MySQL
Oracle Cloud Infrastructure
Oracle Database
PwC Check-In
PyTorch
TensorFlow
Ubuntu
scikit-image

Integrations

Apache Hive
Apache Spark
Docker
Impala
Keras
Kinetica
MXNet
MySQL
Oracle Cloud Infrastructure
Oracle Database
PwC Check-In
PyTorch
TensorFlow
Ubuntu
scikit-image

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

MLReef

Country

United States

Website

www.mlreef.com

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

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

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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