This is a simple implementation of RBM learning algorithm written in Python
which uses numpy
package to speed up matrix calculations.
To run RBM learning algorithm on MNIST dataset with default parameters, type
python rbm.py
Otherwise you can specify all parameters yourself
python rbm.py <num_examples> <num_hidden_units> <num_epochs> <learn_rate>
This will train an RBM on training examples and then try to reconstruct the test images given the learned weights. Both original test images and the reconstructed test images will then be saved in Output/
folder.
Please note this project requires Python 3.x to run. It also requires the numpy
package.