Why normalizing your clinical and claims data into standard terminologies is critical to supporting forward-thinking initiatives such as big data analytics, population health management and semantic ...

It’s tempting just to replicate all databases in the cloud, but it’s a much better approach to get your data house in order as part of the move. Last week I discussed database normalization as a best ...

Arguably, the two biggest challenges in the FAST ecosystem are managing the ad experience and delivering ROI for the brands that support the platform. Evan Shapiro, CEO, ESHAP, Patrick Courtney, SVP, ...

We used dual embeddings for English and Bulgarian languages, encoding both syntactic and polarity information for the words. The embeddings were subsequently aligned so that they were in the same ...

It’s time for traders to start paying attention to a data revolution underway that is increasingly impacting their ability to both scale their business and provide value to their clients. Capital ...

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 ...

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, ...

This article explains how to programmatically normalize numeric data for use in a machine learning (ML) system such as a deep neural network classifier or clustering algorithm. Suppose you are trying ...

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 ...