<commit_before># cupydle [![Build Status](https://travis-ci.org/lerker/cupydle.svg?branch=master)](https://travis-ci.org/lerker/cupydle) [![GitHub issues](https://img.shields.io/github/issues/lerker/cupydle.svg?style=plastic)](https://github.com/lerker/cupydle/issues) [![GitHub license](https://img.shields.io/badge/license-Apache%202-blue.svg?style=plastic)](https://raw.githubusercontent.com/lerker/cupydle/master/LICENSE) [![GitHub forks](https://img.shields.io/github/forks/lerker/cupydle.svg?style=plastic)](https://github.com/lerker/cupydle/network) [![todofy badge](https://todofy.org/b/lerker/cupydle)](https://todofy.org/r/lerker/cupydle)

**CU**da**PY**thon**D**eep**LE**arning Machine Learning

Introducción
============
_cupydle_ is the fastest and easiest way to use Restricted Boltzmann
Machines (RBMs). RBMs are a class of probabilistic models that can discover
hidden patterns in your data. _cupydle_ provides all the necessary methods with
a pythonic interface, and moreover, all methods call blazing fast C code. The
code can also run transparently on GPU thanks to
Theano (http://deeplearning.net/software/theano/).


:white_check_mark: finished

:negative_squared_cross_mark: not done

:interrobang: in progress or not finished

:bangbang: very important and not done



Functionality:

- Restricted Boltzmann Machine Training
  - [x] With n-step Contrastive Divergence (CD)<commit_msg>cambios menores en el readme<commit_after># cupydle [![Build Status](https://travis-ci.org/lerker/cupydle.svg?branch=master)](https://travis-ci.org/lerker/cupydle) [![GitHub issues](https://img.shields.io/github/issues/lerker/cupydle.svg?style=plastic)](https://github.com/lerker/cupydle/issues) [![GitHub license](https://img.shields.io/badge/license-Apache%202-blue.svg?style=plastic)](https://raw.githubusercontent.com/lerker/cupydle/master/LICENSE) [![GitHub forks](https://img.shields.io/github/forks/lerker/cupydle.svg?style=plastic)](https://github.com/lerker/cupydle/network) [![todofy badge](https://todofy.org/b/lerker/cupydle)](https://todofy.org/r/lerker/cupydle)

**CU**da**PY**thon**D**eep**LE**arning Machine Learning

Introducción
============
_cupydle_ es una libreria simple y sencilla, que provee todas las funcionalidades necesarias para la ejecucion de Redes de Creencia Profunda (DBN) sobre placas de procesamiento grafico para proposito general (GP-GPU).
_cupydle_ posse una inteface 'pythonica', y además, el codigo puede ser ejecutado de forma transparente tanto en GPU como en CPU gracias a Theano (http://deeplearning.net/software/theano/).


:white_check_mark: finished

:negative_squared_cross_mark: not done

:interrobang: in progress or not finished

:bangbang: very important and not done



Funcionalidades:

- Maquinas de Boltzmann Restringidas
  - Entrenamiento
    - [x] Algoritmo de Divergencia Constrastiva de n pasos de Gibbs (CD_n)
    - [x] Algoritmo de Divergencia Constrastiva Persistente de n pasos de Gibbs (PCD_n)
    - [:interrobang:] Weight decay, momentum, batch-learning
    - [x] Unidades Ocultas Binarias.
    - [ ] Unidades Ocultas Gausianas.


- Restricted Boltzmann Machine Training
  - [x] With n-step Contrastive Divergence (CD)
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{'dir': 'git-commits-cleaned', 'id': '4950808', 'n_tokens_mistral': 1152, 'n_tokens_neox': 1080, 'n_words': 246}