Archives for aleatoric uncertainty
Machine learning heavily relies on probability theory. Hence, managing uncertainty (read imperfect or incomplete information) is key to machine learning (ML) projects. Ideally, deep learning makes it possible to produce dependable predictions on data from the same distribution the models were trained on. However, there are often disparities in the distribution of data on which […]