the power of supervised and unsupervised conclusion part iv deep unsupervised learning using tensorflow and keras recommender systems using restricted boltzmann machines boltzmann machines restricted boltzmann machines recommender systems collaborative filtering the netflix prize movielens dataset data preparation define the cost functionmean squared error perform baseline experiments matrix factorization one latent factor three latent factors five latent factors collaborative filtering using rbms rbm neural network architecture build the components of the rbm class train rbm recommender system conclusion feature detection using deep belief networks deep belief networks in detail mnist image classification restricted boltzmann machines build the components of the rbm class generate images using the rbm model view the intermediate feature detectors train the three rbms for the dbn examine feature detectors view generated images the full dbn how training of dbn works train the dbn how unsupervised learning helps supervised learning generate images to build better image classifier viii table of contents