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 ...

Single-cell RNA sequencing (scRNA-seq) has transformed the field of transcriptomics by making it possible for researchers to address fundamental questions that could not be tackled by bulk-level ...

Without normalization, the large magnitudes of the income data relative to the age data would make the neural network training process more difficult than with normalized data, because changes to the ...

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 ...

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 ...

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, ...

Understanding and correcting variability in western blot experiments is essential for reliable quantitative results. Experimental errors from pipetting, gel transfer, or sample differences can distort ...

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 ...

There are many types of experimental methods that often use normalization to fix the differences induced by factors other than what is immediately being analyzed. In particular, normalization can be ...