The shortest definition of embeddings?

Roy Keyes

19 Nov 2022 - This is a post on my blog. Get the RSS feed!

A Stable Diffusion generated image of an embedding space

Embeddings are a very important concept in deep learning and several related techniques. They are powerful and flexible and at the core of many modern machine learning systems. But, they are also tricky to describe.

Here is my attempt to create a very succinct definition and description of embeddings.

Embeddings are learned transformations to make data more useful

What does this mean?

Embeddings are incredibly useful for many data related tasks. They are especially useful for things like search (e.g. what other images are like this one?) and recommendations. More generally they are useful for working with data that is not inherently numeric, such as text, images, or audio.

While I didn't touch on the technical aspects of creating or using embeddings, hopefully this is helpful as a conceptual overview for you.

Learn more in my book

If you found this post useful, you'll probably also find my book useful: Zefs Guide to Deep Learning. Zefs Guide to Deep Learning covers the most important topics in deep learning in a conceptual, easy to understand way, but enough technical detail to help data scientists and machine learning engineers solidify their understanding of what's really going on.