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

Non-negative matrix factorization

Project Activity

See All Activity >

Categories

Machine Learning

License

GNU General Public License version 3.0 (GPLv3)

Follow GPUMLib

GPUMLib Web Site

Other Useful Business Software
Compliant and Reliable File Transfers Backed by Top Security Certifications Icon
Compliant and Reliable File Transfers Backed by Top Security Certifications

Cerberus FTP Server delivers SOC 2 Type II certified security and FIPS 140-2 validated encryption.

Stop relying on non-certified, legacy file transfer tools that creak under the weight of modern security demands. Get full audit trails, advanced access controls and more supported by an award-winning team of experts. Start your free 25-day trial today.
Start Free Trial
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of GPUMLib!

Additional Project Details

Intended Audience

Developers, Education, Engineering, Science/Research

User Interface

.NET/Mono, Console/Terminal, Qt

Programming Language

C#, C++

Related Categories

C# Machine Learning Software, C++ Machine Learning Software

Registered

2010-02-22
Report inappropriate content