In a traditional neural network, weights are assigned as a single value or point estimate, whereas in BNN, weights are considered a probability distribution. These probability distributions of network weights are used to estimate the uncertainty in weights and predictions. Figure-1 shows a schematic diagram of a BNN where weights are normally distributed. The posterior of the weights are calculated using Bayes theorem as: