This chapter discusses how Boltzmann machines can be used for collaborative filtering.

Even though discrete sampling of the contrastive divergence algorithm is used for learning the model, the final phase of inference is done using real-valued sigmoid and softmax activations. Discuss how you can use this fact to your advantage in order to fine-tune the learned model with backpropagation.