Entity Embeddings

Entity Embeddings are a technique for applying deep learning to tabular data, representing categorical data in information systems as multi-dimensional vectors. This approach aims to capture complex relationships between categorical features, enhancing the model's understanding and predictive power of non-numeric data, thereby playing a significant role in recommendation systems, user behavior analysis, and other fields.