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Save hundreds of developer hours with components built for SaaS applications.
The #1 Embedded Analytics Solution for SaaS Teams.
Whether you want full self-service analytics or simpler multi-tenant security, Qrvey’s embeddable components and scalable data management remove the guess work.
Open Source Java platform for Optimization, DoE, and Learning.
OpenDino is an open source Java platform for optimization, design of experiment and learning.
It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules".
Implemented Modules
Evolutionary Algorithms:
- CMA-ES
- (1+1)-ES
- Differential Evolution
Deterministic optimization algorithm:
- SIMPLEX
Learning:
- a simple Artificial Neural Net
Optimization problems:
- test functions
- interface for executing...
NEW OPTIMIZATION TECHNOLOGY & PLANNING EXPERIMENT. Technology is designed for multidimensional optimization practical problems with continuous object functions. Technology higher efficiency than traditional optimization methods.
A self-contained, fully configurable Java "game" to simulate multi-species evolution. Design species by optionally specifying every attribute; modify any or all environmental settings; let them loose to eat, fight, procreate, die, and Evolve!
X-GAT (XML-based Genetic Algorithm Toolkit) is a Java framework to optimize problems with Genetic Algorithms (GAs). Differently from other frameworks, X-GAT contains ready-to-use GAs implementations and new features can be easily added.
Deploy Red Hat Enterprise Linux on Microsoft Azure for a secure, reliable, and scalable cloud environment, fully integrated with Microsoft services.
Red Hat Enterprise Linux (RHEL) on Microsoft Azure provides a secure, reliable, and flexible foundation for your cloud infrastructure. Red Hat Enterprise Linux on Microsoft Azure is ideal for enterprises seeking to enhance their cloud environment with seamless integration, consistent performance, and comprehensive support.
MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.