What is embedding-based feature engineering?

Embeddings convert categorical or textual data into dense numerical vectors capturing semantic relationships.

Embeddings map high-dimensional sparse data into low-dimensional dense vectors learned by neural networks. They capture similarity relationships between entities, making them powerful for NLP and recommendation systems.