Applications of deep learning in high-risk domains such as healthcare and autonomous control require a greater understanding of model uncertainty, and the field of bayesian deep learning seeks to provide efficent methods for doing so. We examine the basics of this field and one recent result from it: the Bayes by Backprop algorithm.