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.

Features

  • Multiple Back-Propagation (MBP)
  • Back-Propagation (BP)
  • Radial Basis Functions (RBF)
  • Non-Negative Matrix Factorization (NMF)
  • Semi-Supervised Non-Negative Matrix Factorization (SSNMF)
  • Restricted Boltzmann Machines (RBM)
  • Deep Belief Networks (DBN)
  • Autonomous Training System (ATS)
  • Support Vector Machines (SVM)
  • Self Organizing Maps (SOM)

Project Samples

Project Activity

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Categories

Machine Learning

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GPUMLib Web Site

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Additional Project Details

Intended Audience

Science/Research, Education, Developers, Engineering

User Interface

.NET/Mono, Console/Terminal, Qt

Programming Language

C#, C++

Registered

2010-02-22