Mini toolsDefinition
Dense vector representations of data that capture semantic meaning in a form usable by machine learning models. These enable efficient processing of text images or other data types.
Detailed Explanation
Embeddings are learned vector representations that map high-dimensional data into a lower-dimensional space while preserving semantic relationships. They capture meaningful features and similarities between items making them useful for various downstream tasks. Embeddings can represent words sentences images users or any other type of data in a format suitable for machine learning models.
Use Cases
Semantic search Recommendation systems Natural language processing Information retrieval
