Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
AutoScientist is an innovative system designed to enhance and automate the comprehensive research process involved in model training and alignment, empowering more teams to influence and improve the AI technologies they rely on. Although model training and reinforcement learning serve as some of the most effective methods for model development, achieving success in these areas can be particularly challenging outside of leading research facilities due to issues like catastrophic forgetting, overfitting on limited or subpar datasets, and conflicting training signals. AutoScientist automatically co-optimizes both data and model training strategies, continuously refining both aspects until the outcome aligns with the user’s objectives. While Adaptive Data focuses on optimizing inputs, AutoScientist is dedicated to refining the model, effectively executing the entire research cycle from start to finish, ensuring users receive models that are finely tuned to their specific goals. This self-sustaining process allows for simultaneous co-optimization of data and training strategies, iterating seamlessly until the model achieves the desired behavior as specified by the user, ultimately leading to enhanced performance and usability.
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 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
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
No
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
AutoScientist
Country
United States
Website
www.adaptionlabs.ai/blog/autoscientist
Vendor Details
Company Name
Oracle
Founded
1977
Country
United States
Website
www.oracle.com/data-science/machine-learning/
Product Features
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