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Data Science & ML

Embeddings

/ɪmˈbedɪŋz/

Definition

Dense vector representations of data (text, images) that capture semantic meaning, enabling similarity search.

Example in context

"We store document embeddings in a vector database — semantic search finds related articles by cosine similarity."

Related terms

  • RAG — Retrieval-Augmented Generation — augmenting LLM prompts with relevant retrieved documents to ground responses in facts.

Practice this term

Master Embeddings in context by working through exercises in the Data Science & ML module. You'll see the term used in real engineering scenarios with multiple-choice, fill-in-the-blank, and matching drills.

Practice in exercises → Browse all words

Frequently Asked Questions

What does "Embeddings" mean?

Dense vector representations of data (text, images) that capture semantic meaning, enabling similarity search.

How do you pronounce "Embeddings"?

"Embeddings" is pronounced /ɪmˈbedɪŋz/.

Can you use "Embeddings" in a sentence?

"We store document embeddings in a vector database — semantic search finds related articles by cosine similarity."