Mini toolsDefinition
The number of dimensions in the vector space used to represent data in AI models.
Detailed Explanation
A hyperparameter that determines the dimensionality of the vector representations created by embedding layers. It affects the model’s capacity to capture relationships and patterns in the input data, with larger sizes allowing for more complex representations but requiring more computational resources.
Use Cases
Word embeddings in NLP, User behavior modeling in recommendation systems, Feature representation in deep learning
