This library implements various machine learning methods. The purpose here is mostly educational (for my own and hopefully others') and I aim for clarity rather than efficiency. Note that this is a work in progress! So far the library contains implementations for

• Multilayer Perceptrons
• Restricted Boltzmann Machines and Deep Belief Networks (with support for GPUs through gnumpy)
• k-Means clustering
• Principal Components Analysis
• Metric learning
  • Method of Schultz, M., & Joachims, T. (2003) that learns a diagonal distance metric matrix
  • A variant of Schultz, M., & Joachims, T. (2003) that learns a low-rank distance metric matrix