📚 node [[dimensions|dimensions]]
Welcome! Nobody has contributed anything to 'dimensions|dimensions' yet. You can:
  • Write something in the document below!
    • There is at least one public document in every node in the Agora. Whatever you write in it will be integrated and made available for the next visitor to read and edit.
  • Write to the Agora from social media.
    • If you follow Agora bot on a supported platform and include the wikilink [[dimensions|dimensions]] in a post, the Agora will link it here and optionally integrate your writing.
  • Sign up as a full Agora user.
    • As a full user you will be able to contribute your personal notes and resources directly to this knowledge commons. Some setup required :)
⥅ related node [[dimensions]]
⥅ related node [[week4 numpy in two dimensions lab]]
⥅ node [[dimensions]] pulled by Agora
📓 garden/KGBicheno/Artificial Intelligence/Introduction to AI/Week 3 - Introduction/Definitions/Dimensions.md by @KGBicheno

dimensions

Go back to the [[AI Glossary]]

Overloaded term having any of the following definitions:

The number of levels of coordinates in a Tensor. For example:
    A scalar has zero dimensions; for example, ["Hello"].
    A vector has one dimension; for example, [3, 5, 7, 11].
    A matrix has two dimensions; for example, [[2, 4, 18], [5, 7, 14]].

You can uniquely specify a particular cell in a one-dimensional vector with one coordinate; you need two coordinates to uniquely specify a particular cell in a two-dimensional matrix.

The number of entries in a feature vector.

The number of elements in an embedding layer.
📖 stoas
⥱ context
← back
ai glossary

↑ pushing here
(none)

↓ pulling this
(none)
→ forward
(none)
🔎 full text search for 'dimensions|dimensions'