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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.
... implemented units are then automatically integrated with the rest of the library.
The base of available algorithms is steadily increasing and includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others.
Project planning software using the Results Based Management framework
[Caveat Emptor] The dialogs are mostly just layouts without funcionality. The only things that function yet are: RBM lexicon, About, and the work and break timers.
This software is just in the concept stages right now, but the hope is to be able to put out a tool that aid and development agencies, such as CIDA etc, and not-for-profit NGOs can use to help plan, manage, and report on their projects.
Build a foundation for data security and disaster recovery to fit your clients’ needs no matter the budget.
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An open source library for artificial neural networks.
OpenANN is a C++ library that provides implementations for modular artificial neural networks with only a few dependencies and additional Python bindings.
An experimental unsupervised learning method for improvising jazz melodies, based on restricted Boltzmann machines (RBMs) layered into Deep Belief Networks (forms of neural networks).
Linflix is an open-source C++ collection of tools and algorithms for processing the Netflix Prize dataset and calculating predictions for missing rating data.
Dinrhiw2 - machine learning library and tools (neural networks) in C++
Machine learning C++ library. Linear algebra (PCA), splines hermite curve interpolation, neural networks (feedforward, recurrent, RBM, bayesian), Hidden markov model (HMM), Hamiltonian Monte Carlo sampling for neural networks etc. Uses BLAS (OpenBLAS, Intel MKL) to speed up linear algebra.
Software is developed by Tomas Ukkonen.