ENH added Restricted Boltzmann machines
30% speed-up thanks to in-place binomial

From https://gist.github.com/359323.
ENH 12% RBM speedup with ingenious ordering of operations

+ inplace gradients for components_, 2% speed-up
rename h_samples to h_samples_
added URI for RBM reference
improved docstring for transform
renamed _sigmoid to _logistic_sigmoid
use double backquotes around equations
logistic_sigmoid moved to function
transposed components_, no performance penalty
only compute pseudolikelihood if verbose=True
more accurate pseudo-likelihood
use iteration terminology instead of epochs in RBM
default n_components from 1024 to 256
clarify some method names (ex: mean_h -> mean_hiddens)
added epoch time
ENH RBM example
switched to digits
moved rbms to neural_networks module
add tests for rbm