A technique used in AI to convert categorical variables into a numerical form for use in machine learning algorithms, improving model performance by capturing the underlying relationships between categories.
For instance, an embedding of a categorical variable like ‘color’ could map ‘red’ to the vector (0.5, 0.3, 0.2), while mapping ‘blue’ to the vector (-0.7, -0.4, 0.1).