restricted-boltzmann-machines | Restricted Boltzmann Machines in Python | Machine Learning library

restricted-boltzmann-machines is a Python library typically used in Artificial Intelligence, Machine Learning applications. restricted-boltzmann-machines has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However restricted-boltzmann-machines build file is not available. You can download it from GitHub.

Suppose you ask a bunch of users to rate a set of movies on a 0-100 scale. In classical factor analysis, you could then try to explain each movie and user in terms of a set of latent factors. For example, movies like Star Wars and Lord of the Rings might have strong associations with a latent science fiction and fantasy factor, and users who like Wall-E and Toy Story might have strong associations with a latent Pixar factor. Restricted Boltzmann Machines essentially perform a binary version of factor analysis. (This is one way of thinking about RBMs; there are, of course, others, and lots of different ways to use RBMs, but I'll adopt this approach for this post.) Instead of users rating a set of movies on a continuous scale, they simply tell you whether they like a movie or not, and the RBM will try to discover latent factors that can explain the activation of these movie choices.