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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Decanter AI is a no-code AI tool that helps data scientists, domain specialists, and business stakeholders design and deploy AI solutions in a seamless manner. Data is at the core of all business growth. But it also presents new challenges. Decanter AI's advanced AI technologies make digital transformation as simple as eating a bagel. Decanter AI uses automated Machine Learning (AutoML), an automation of the machine-learning process, to assist enterprises with AI driven decision making. It also generates business value using enterprise data. Decanter AI provides enterprises with world-class technologies for machine learning through an intuitive interface. It allows enterprises to solve business problems using an AI-driven method by rapidly building, test and deploying highly accurate models.

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 Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Hive No 
Apache Spark No 
Impala No 
Kinetica No 
MySQL No 
Oracle Cloud Infrastructure No 
Oracle Database No 
PwC Check-In No 

Integrations

Apache Hive Yes 
Apache Spark Yes 
Impala Yes 
Kinetica Yes 
MySQL Yes 
Oracle Cloud Infrastructure Yes 
Oracle Database Yes 
PwC Check-In Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

MoBagel Inc.

Founded

2015

Country

United States

Website

mobagel.com/decanter-ai/

Vendor Details

Company Name

Oracle

Founded

1977

Country

United States

Website

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

Product Features

Predictive Analytics

AI / Machine Learning Yes 
Benchmarking No 
Data Blending No 
Data Mining Yes 
Demand Forecasting Yes 
For Education Yes 
For Healthcare Yes 
Modeling & Simulation Yes 
Sentiment Analysis No 

Product Features

Data Science

Access Control No 
Advanced Modeling No 
Audit Logs No 
Data Discovery No 
Data Ingestion No 
Data Preparation No 
Data Visualization No 
Model Deployment No 
Reports No 

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives

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