When normalizing data structures, attributes congregate around the business keys that identify the grain at which those attributes derive their values. Attributes directly related to a person, ...

AI training and inference are all about running data through models — typically to make some kind of decision. But the paths that the calculations take aren’t always straightforward, and as a model ...

Occasionally one may hear that a data model is “over-normalized,” but just what does that mean? Normalization is intended to analyze the functional dependencies across a set of data. The goal is to ...

Dr. James McCaffrey of Microsoft Research uses a full code sample and screenshots to show how to programmatically normalize numeric data for use in a machine learning system such as a deep neural ...

We collected a unique pair of microRNA sequencing data sets for the same set of tumor samples; one data set was collected with and the other without uniform handling and balanced design. The former ...