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MLboost: MachineLearning boost library in Python. MLboost main goal is to speedup any MachineLearning projects by simplifying data preprocessing, features selection and data visualisation. Design by MachineLearning practitioners to let them do ML...;)
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
Optex Analyzer is a software to analyze and compare algorithms to solve approximately optimization problems. It has a GUI that allows select a set of input files containing raw algorithm results. The analysis is shown with tables and charts.
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.
RILA is a machinelearning software for relational data. It is able to find frequent patterns in a set of connected tables stored in relational database management systems.
A java tool for anytime and interactive sequence mining. Aims at providing users with a way of analyzing her activity traces and extract activity schemes from them.
A Python function library to extract EEG feature from EEG time series in standard Python and numpy data structure. Features include classical spectral analysis, entropies, fractal dimensions, DFA, inter-channel synchrony and order, etc.
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.
A HTML scraper that uses machinelearning frameworks to extract labelled fields from raw HTML. The project also involves the development of a tool to display the semi structured data generated by the scraper component.
Platform supporting machinelearning on different objects by different modification of the JSM method (for now). Predicates for the JSM method are written in CLIPS.Objects and modification of the JSM method have to written on one of .NET languages.
Blunder is an automated tool for analyzing chained exceptions in Java. It's usefull for classify, generate a customized error message and a list for possible solutions.
A project aims to develop a system which trains LDA model in distributed enviorenment. I studied Hadoop based solution and found that Hadoop is not fit for distributed LDA training case. In this project I implement a platform based on socket.
A C++ library for machinelearning within dynamic systems. It provides methods such as the Kalman, unscented Kalman, and particle filters and smoothers, as well as useful classes such as common probability distributions and stochastic processes.
T-Rex (Trainable Relation Extraction) is a highly configurable machinelearning-based Information Extraction from Text framework, which includes tools for document classification, entity extraction and relation extraction.
TimeSleuth discovers temporal decision rules. It also judges the (a)causality of the rules. TimeSleuth can discover rules that involve time: {if (rainy_yesterday = true) then rainy_today = true}, or {if (rainy_tomorrow = true) then rainy_today = true}.
A set of services to allow for polling remote sites for data, displaying it on the local machine requesting said data, and moving that data anywhere else it needs to go.
Zabal6 is a machinelearning student tool based on decision tree learning, focused in the area of knowledge discovery (data mining), and inspired on See5. Zabl6 is a C++ program for Linux and windows O.S, with a intuitive graphical interface.
Machinelearning toolkit for unsupervised and semi-supervised clustering that demonstrates excellent results on real-world data (see Bekkerman et al. ICML-2005 and ECML-2006).
PCP (Pattern Classification Program) is an open-source machinelearning program for supervised classification of patterns. PCP is a binary executable running on Linux and Windows (under Cygwin environment).
MultiBoost is a C++ implementation of the multi-class AdaBoost algorithm. AdaBoost is a powerful meta-learning algorithm commonly used in machinelearning. The code is well documented and easy to extend, especially for adding new weak learners.