Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Facilitate collaboration between data scientists and application developers on machine learning initiatives. Create, load, enhance, and evaluate models and their integrations prior to making them accessible to end-users for incorporation into active applications. Alleviate the workload of data science teams and enhance decision-making processes by enabling the storage and sharing of machine learning models throughout the organization. Automatically disseminate updates to ensure that modifications to models in production are promptly reflected. Boost operational efficiency by delivering machine learning-driven insights directly within any web-based business application. Our user-friendly, drag-and-drop browser extension allows analysts and business users to seamlessly incorporate models into any web application without the need for coding, thereby democratizing access to advanced analytics. This approach not only streamlines workflows but also empowers users to make data-driven decisions with confidence.
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
No
API Access
Has API
Yes
Integrations
Apache Spark
Yes
Apache Hive
No
AveeCare
Yes
Impala
No
Kinetica
No
Microsoft 365
Yes
MySQL
No
Oracle Artificial Intelligence
Yes
Oracle Cloud Infrastructure
No
Oracle Database
No
Integrations
Apache Spark
Yes
Apache Hive
Yes
AveeCare
No
Impala
Yes
Kinetica
Yes
Microsoft 365
No
MySQL
Yes
Oracle Artificial Intelligence
No
Oracle Cloud Infrastructure
Yes
Oracle Database
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
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
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
No
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
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
AI Squared
Founded
2021
Country
United States
Website
squared.ai/
Vendor Details
Company Name
Oracle
Founded
1977
Country
United States
Website
www.oracle.com/data-science/machine-learning/
Product Features
Artificial Intelligence
Chatbot
No
For Healthcare
No
For Sales
No
For eCommerce
No
Image Recognition
No
Machine Learning
No
Multi-Language
No
Natural Language Processing
No
Predictive Analytics
No
Process/Workflow Automation
No
Rules-Based Automation
No
Virtual Personal Assistant (VPA)
No
Integration
Dashboard
No
ETL - Extract / Transform / Load
No
Metadata Management
No
Multiple Data Sources
No
Web Services
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
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