Understanding Zero-Shot Learning — Making ML More Human
An intuitive overview of how a model can recognize what it hasn’t seen.
Introduction — What is Zero-Shot Learning?
Zero-shot learning allows a model to recognize what it hasn’t seen before.
Imagine you’re tasked with designing the latest and greatest machine learning model that can classify all animals. Yes, all animals.
Using your machine learning knowledge, you immediately understand that we need a labeled dataset with at least one example for every single animal. There’s 1,899,587 described species in the world, so you’re gonna need a dataset with roughly 2 million different classes.
Yikes.
As you’ve probably noticed by now, getting large quantities of high quality labeled data is hard. Very hard.
It doesn’t help when there are a gazillion different classes (i.e. animal species) that your model has to learn.