Machine learning software to solve data mining problems
Weka is a collection of machine learning algorithms for solving real-world data mining problems. It is written in Java and runs on almost any platform. The algorithms can either be applied directly to a dataset or called from your own Java code.
Fast C++ matrix library with easy to use functions and syntax, deliberately similar to Matlab. Uses template meta-programming techniques. Also provides efficient wrappers for LAPACK, BLAS and ATLAS libraries, including high-performance versions such as OpenBLAS and Intel MKL. Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. For more details, see http://arma.sourceforge.net
Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
Java Neural Network Framework
Neuroph is lightweight Java Neural Network Framework which can be used to develop common neural network architectures. Small number of basic classes which correspond to basic NN concepts, and GUI editor makes it easy to learn and use.
A python module for hyperspectral image processing
Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more.
A Multi-label Extension to Weka
Multi-label classifiers and evaluation procedures using the Weka machine learning framework.
Machine learning algorithms for advanced analytics
OpenNN is a software library written in C++ for advanced analytics. It implements neural networks, the most successful machine learning method. Some typical applications of OpenNN are business intelligence (customer segmentation, churn prevention…), health care (early diagnosis, microarray analysis…) and engineering (performance optimization, predictive maitenance…). OpenNN does not deal with computer vision or natural language processing. The main advantage of OpenNN is its high performance. This library outstands in terms of execution speed and memory allocation. It is constantly optimized and parallelized in order to maximize its efficiency. The documentation is composed by tutorials and examples to offer a complete overview about the library. OpenNN is developed by Artelnics, a company specialized in artificial intelligence.
Music research software
jMIR is an open-source software suite implemented in Java for use in music information retrieval (MIR) research. It can be used to study music in the form of audio recordings, symbolic encodings and lyrical transcriptions, and can also mine cultural information from the Internet. It also includes tools for managing and profiling large music collections and for checking audio for production errors. jMIR includes software for extracting features, applying machine learning algorithms, applying heuristic error error checkers, mining metadata and analyzing metadata.
It's possible for machines to become self-aware.
We believe that it's possible for machines to become self-aware, but may not exhibit human-like thought processes. This project is a quest for conscious artificial intelligence. We will develop prototypes while we go for our main goal. Our steps will be 1) Develop a Learning/Predictive Module. 2) Develop a Planning Module based on the learning/predictive module. 3) Develop a Plan Optimization Module so plans built in the previous module can be optimized. 4) Develop a Decision Making Engine based on previous planning. 5) Develop prototypes of the artificial creature. 6) Publish some academic papers. And there is the video: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3 mining sites and bringing to the base. At the time the agent is born, it doesn't know how to walk nor it knows that it feels pleasure by mining. He has tact only (blind agent). The video shows learning, planning, executing and optimizing plans.
Scene is a computer vision framework that performs background subtraction and object tracking, using two traditional algorithms and three more recent algorithms based on neural networks and fuzzy classification rules. For each detected object, Scene sends TUIO messages to one or several client applications. The present release features GPU accelerated versions of all the background subtraction methods and morphological post processing of the object blobs with dilation and erosion filters, implemented in OpenCL. The framework was mainly designed as a toolkit for the rapid development of interactive art projects that explore dynamics of complex environments. The Scene GUI runs and compiles under Windows, Linux, and MacOS X, and is available in both 32 bit and 64 bit versions.
Open source software for training neural networks
Multiple Back-Propagation is an open source software application for training neural networks with the backpropagation and the multiple back propagation algorithms. Currently this project is also hosted at http://code.google.com/p/multiplebackpropagation
A framework for the development of intelligent systems.
QSMM, a recursive acronym for "QSMM State Machine Model", is a framework for learning finite automatons that perform goal-directed interaction with entities which exhibit deterministic or stochastic behavior. The learning process can be carried out in real time together with the interaction process. A basic building block for supporting state models of finite automatons is adaptive probabilistic mapping, which for an argument from its domain returns more often results that maximize or minimize values of one or more objective functions. Finite automatons can be represented by assembler programs with user-defined instructions that perform effective work. To assist in the learning of a finite automaton, a template for its state model can be provided as an assembler program with probabilistic jump instructions. The operating principle behind the framework resembles the Boltzmann machine.
GPU Machine Learning Library. This library aims to provide machine learning researchers and practitioners with a high performance library by taking advantage of the GPU enormous computational power. The library is developed in C++ and CUDA.
An open source optical flow algorithm framework for scientists and engineers alike.
speech recognition software for Polish language
Software for speech recognition in Polish language. Large vocabulary continuous speech recognition (LVCSR) and Commands. SkryBot recognises speech in Polish language and changes it into text by using: 1.microphone, 2.sound files (turned off in demo version). SkryBot recognises dictated speech and converts it into text. This means, that if you speak to the microphone or you use earlier recorded sound file, SkryBot will change it into text. SkryBot offers you: 1. audio conversion and cutting sound files into smaller ones, 2. searching for words or phrases in sound files (recognised by SkryBot), 3. editing sound files and automatic cutting off long silence parts in the recording, 4. improving accuracy of recognition. Versions of SkryBot: 1. SkryBot Prawo - for courts, lawyers, police, 2. SkryBot Administracyjny - for civil and government administration, 3. SkryBot Medycyna Rodzinna - for doctors, hospitals. https://sourceforge.net/p/skrybotdomowy/wiki/Home
A Weka Plugin that uses a Genetic Algorithm for Data Oversampling
Weka genetic algorithm filter plugin to generate synthetic instances. This Weka Plugin implementation uses a Genetic Algorithm to create new synthetic instances to solve the imbalanced dataset problem. See my master thesis available for download, for further details.
CIntruder - OCR Bruteforcing Toolkit
Captcha Intruder is an automatic pentesting tool to bypass captchas.
Scientific computing, machine learning and computer vision for .NET
The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.
This project aims to develop and share fast frequent subgraph mining and graph learning algorithms. Currently we release the frequent subgraph mining package FFSM and later we will include new functions for graph regression and classification package
This project relates to research work at Imperial College conducted by members of the SPIKE (Structured and Probabilistic Intelligent Knowledge Engineering), including in particular logic-based learning systems such as TAL, ASPAL and ILASP.
Chat bot and free roaming AI in batch
Included in this project is a simple chat bot, a battle AI, and a swarm based free roaming AI.
A Java package for the LDA and DMM topic models
The Java package jLDADMM is released to provide alternative choices for topic modeling on normal or short texts. It provides implementations of the Latent Dirichlet Allocation topic model and the one-topic-per-document Dirichlet Multinomial Mixture model (i.e. mixture of unigrams), using collapsed Gibbs sampling. In addition, jLDADMM supplies a document clustering evaluation to compare topic models. See the usage of jLDADMM in its website at http://jldadmm.sourceforge.net/
End-to-end big data in a massively scalable supercomputing platform.
HPCC Systems® (www.hpccsystems.com) from LexisNexis® Risk Solutions is a proven, open source solution for Big Data insights that can be implemented by businesses of all sizes. With HPCC Systems, developers can design applications with Big Data at their core, enabling businesses to better analyze and understand data at scale, improving business time to results and decisions. HPCC Systems offers a consistent data-centric programming language, two processing platforms and a single, complete end-to-end architecture for efficient processing. Read our blog (http://hpccsystems.com/blog ), or connect with us on Twitter (@hpccsystems), Facebook (https://www.facebook.com/hpccsystems ) and LinkedIn (http://www.linkedin.com/company/hpcc-systems) HPCC Systems is available on AWS & can be configured through the Instant Cloud Solution. The download here is a VM.
All future developments will be implemented in the new MATLAB toolbox SciXMiner, please visit https://sourceforge.net/projects/scixminer/ to download the newest version. The former Matlab toolbox Gait-CAD was designed for the visualization and analysis of time series and features with a special focus to data mining problems including classification, regression, and clustering.