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 ...

To some extent, many organizations, if not all, suffer from some form of performance deviation. This can manifest itself in any goal or standard against which organizations may measure themselves.

A topic that's often very confusing for beginners when using neural networks is data normalization and encoding. Because neural networks work internally with numeric data, binary data (such as sex, ...

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 ...

Responses of neurons that integrate multiple sensory inputs are traditionally characterized in terms of a set of empirical principles. However, a simple computational framework that accounts for these ...