Chapter 2. Training Data Concepts
Schema Deep Dive Introduction
What do you want your AI system to do? How will it accomplish it? What methods are you going to use? In this chapter I dive into some of the foundational concepts around supervised training data.
The real world is messy. And often commercial applications require a level of detail thatâs far more specific then high level labels. There are many ways to structure this. In general these concepts exist as âpivot pointsâ in the application.
I will introduce the core concepts around Training Data Schema - a paradigm for encoding Who, What, Where, How & Why. The Schema is the overall representation of Labels, Attributes, their Relation to each other. And more. Itâs how we represent the meaning of what something is, where it is and more.
Info box?: Schema is also known as Ontology or Label Setup.
This builds on the high level concepts of Labels and Attributes ...