A machine learning model that uses probabilistic layers regression, modelled using TensorFlow. Probabilistic layers regression is a type of linear regression in which the neurons of the neural network are actually probability calculations. We use the TensorFlow Probability module, and consider 5 cases:

1. There is no uncertainty in the data
2. There is aleatoric uncertainty in the data
3. There is epistemic uncertainty in the data
4. There is both aleatoric and epistemic uncertainty in the data
5. There is functional uncertainty in the data NumPy has been used in the storage of data and Matplotlib has been used to plot the figures