📚 node [[dimensions]]
📓
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
- public document at doc.anagora.org/dimensions
- video call at meet.jit.si/dimensions
⥱ context
⥅ related node [[week4 numpy in two dimensions lab]]
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