MoMS (Model Management System) is a model management system for statistical models, a little bit like a database management system. Instead of having tables, we have models that can be updated and queried.
This project is devoted to the creation of an open source Error-Correcting Output Codes (ECOC) library for the Machine Learning community. The ECOC framework is a powerful tool to deal with multi-class categorization problems.
RobGP is a genetic programming system written from the ground up in C++. It's primary goals are efficiency, ease of use, and extensibility. It's distinguishing feature is that it has a modified version of Koza's architecture altering operations.
MultiViL is a tool for multi-view learning. It supports four classifiers (KNN, Naive-Bayes, Rochio and SVM-Perf), four view combining methods (Majority Voting, Borda Count, Dempster-Shafer theory of evidence and PSO) and provides many analisys tools.
A system that shall predict good days and locations for cross country free flying such as paragliding by comparing current weather predictions with statistics about past weather predictions and flights from online contests.
SURIKATA (Syntactic Universal Reasoning for Inducing Kolmogorov Abstract Theories Automatically) is a system for searching large spaces of artifacts and inducing algorithms for generating similar artifacts.
Content Addressable Memory, Multi-Variate Statistics, Data Mining Includes analyzing datasets, extracting patterns, creating empirical expert system. Computes joint probabilities and implements a "belief" as the solution of an equilibrium equation
Parallel Reinforcement Evolutionary Artificial Neural Networks (PREANN) is a framework of flexible multi-layer ANN's with reinforcement learning based on genetic algorithms and a parallel implementation (using XMM registers and NVIDIA's CUDA).
This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
Transform your applications and workflows into powerful agentic systems at global scale.
Gemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
Maui is a multi-purpose automatic topic indexing algorithm. Given a document, Maui automatically identifies its topics. Depending on the task topics are tags, keywords, keyphrases, vocabulary terms, descriptors or Wikipedia titles.
Weekend-robotics enables the dedicated amateur to build a autonomous robot. It runs on a Linux system for high-level operations and offers an interface to the defacto standard hardware abstraction layer in robotics, Player/Stage.
BCAR is a library for the associative classification, which denotes "Boosting
Class Association Rules". BCAR provides a general tool for classification tasks
with various types of input data.
Computer System for Adaptive Intelligent Life :: seeks to create a software system that is capable of learning. The project's ultimate goal is to further the ability of software to both adapt to individual users, and to respond their needs.
Python Machine learning library with multi-core support. Wraps existing ML libraries in order to be able to run and analyse experiments with one front-end API. Currently supports MLP, GA, GP, ESN and RBF algorithms.
{IBA}Miner is an expert system, being developed at the AI-Lab at IBA. The purpose of this software is to provide businesses an easy to use system in which the analysts can easily create and test models and the end-users get predictions for new instances.
A packet dissector driven by machine learning algorithms. You train it to recognize specific types of packets by showing it examples and counterexamples of some packet type, and it will figure out which bits in the packet define it as the type you seek.
Java library devoted to handle Genetic Algorithms and Classifier Systems. It has been engineered to be used into agent based simulation models and to search bounded optimal solutions in wide solution spaces. It runs on distributed clusters.
Signal Processing and Classification Environment in Python using YAML
pySPACE is a modular software for processing of large data streams that has been specifically designed to enable distributed execution and empirical evaluation of signal processing chains. Various signal processing algorithms (so called nodes) are available within the software, from finite impulse response filters over data-dependent spatial filters (e.g. CSP, xDAWN) to established classifiers (e.g. SVM, LDA). pySPACE incorporates the concept of node and node chains of the MDP framework. Due...
A low code unified framework for computer vision and deep learning
Monk is an open source low code programming environment to reduce the cognitive load faced by entry level programmers while catering to the needs of Expert Deep Learning engineers.
There are three libraries in this opensource set.
- Monk Classiciation- https://monkai.org. A Unified wrapper over major deep learning frameworks. Our core focus area is at the intersection of Computer Vision and Deep Learning algorithms.
- Monk Object Detection -...