Beginner · Data
Dimensions
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. Refers to the number of elements or coordinates needed to specify an item in a data structure like a tensor.
Technical Definition
Refers to the number of elements or coordinates needed to specify an item in a data structure like a tensor.
How it works
Dimensions in data often refer to the number of entries in a feature vector or the number of coordinate axes in a tensor. For example, a scalar has zero dimensions, a vector has one dimension, and a matrix has two dimensions. Understanding dimensions is crucial for correctly manipulating and processing data in machine learning.
Related Concepts
- Feature vector — A feature vector is a numerical representation of an example, composed of its feature values, used as input for machine learning models.
- Tensor — A multidimensional array used to represent data in many dimensions, fundamental to deep learning.